Just Accepted
Proactive Conversational AI: A Comprehensive Survey of Advancements and Opportunities
Abstract
Dialogue systems are designed to offer human users social support or functional services through natural language interactions. Traditional conversation research has put significant emphasis on a system’s response-ability, including its capacity to understand dialogue context and generate appropriate responses. However, the key element of proactive behavior – a crucial aspect of intelligent conversations – is often overlooked in these studies. Proactivity empowers conversational agents to lead conversations towards achieving pre-defined targets or fulfilling specific goals on the system side. Proactive dialogue systems are equipped with advanced techniques to handle complex tasks, requiring strategic and motivational interactions, thus representing a significant step towards artificial general intelligence. Motivated by the necessity and challenges of building proactive dialogue systems, we provide a comprehensive review of various prominent problems and advanced designs for implementing proactivity into different types of dialogue systems, including open-domain dialogues, task-oriented dialogues, and information-seeking dialogues. We also discuss real-world challenges that require further research attention to meet application needs in the future, such as proactivity in dialogue systems that are based on large language models, proactivity in hybrid dialogues, evaluation protocols and ethical considerations for proactive dialogue systems. By providing a quick access and overall picture of the proactive dialogue systems domain, we aim to inspire new research directions and stimulate further advancements towards achieving the next level of conversational AI capabilities, paving the way for more dynamic and intelligent interactions within various application domains.
References
[1]
Daniel Adiwardana, Minh-Thang Luong, David R. So, Jamie Hall, Noah Fiedel, Romal Thoppilan, Zi Yang, Apoorv Kulshreshtha, Gaurav Nemade, Yifeng Lu, and Quoc V. Le. 2020. Towards a Human-like Open-Domain Chatbot. CoRR abs/2001.09977 (2020).
[2]
Mohammad Aliannejadi, Zahra Abbasiantaeb, Shubham Chatterjee, Jeffrey Dalton, and Leif Azzopardi. 2024. TREC iKAT 2023: A Test Collection for Evaluating Conversational and Interactive Knowledge Assistants. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, Washington DC, USA, July 14-18, 2024. ACM, 819–829.
[3]
Mohammad Aliannejadi, Julia Kiseleva, Aleksandr Chuklin, Jeff Dalton, and Mikhail S. Burtsev. 2021. Building and Evaluating Open-Domain Dialogue Corpora with Clarifying Questions. In EMNLP.
[4]
Mohammad Aliannejadi, Hamed Zamani, Fabio Crestani, and W. Bruce Croft. 2019. Asking Clarifying Questions in Open-Domain Information-Seeking Conversations. In SIGIR.
[5]
Raviteja Anantha, Svitlana Vakulenko, Zhucheng Tu, Shayne Longpre, Stephen Pulman, and Srinivas Chappidi. 2021. Open-Domain Question Answering Goes Conversational via Question Rewriting. In NAACL-HLT. 520–534.
[6]
Chinmaya Andukuri, Jan-Philipp Fränken, Tobias Gerstenberg, and Noah D. Goodman. 2024. STaR-GATE: Teaching Language Models to Ask Clarifying Questions. CoRR abs/2403.19154 (2024).
[7]
Ashutosh Baheti, Maarten Sap, Alan Ritter, and Mark O. Riedl. 2021. Just Say No: Analyzing the Stance of Neural Dialogue Generation in Offensive Contexts. In EMNLP.
[8]
Jiaqi Bai, Ze Yang, Xinnian Liang, Wei Wang, and Zhoujun Li. 2021. Learning to Copy Coherent Knowledge for Response Generation. In AAAI.
[9]
Yuntao Bai, Saurav Kadavath, Sandipan Kundu, Amanda Askell, Jackson Kernion, Andy Jones, Anna Chen, Anna Goldie, Azalia Mirhoseini, Cameron McKinnon, Carol Chen, Catherine Olsson, Christopher Olah, Danny Hernandez, Dawn Drain, Deep Ganguli, Dustin Li, Eli Tran-Johnson, Ethan Perez, Jamie Kerr, Jared Mueller, Jeffrey Ladish, Joshua Landau, Kamal Ndousse, Kamile Lukosiute, Liane Lovitt, Michael Sellitto, Nelson Elhage, Nicholas Schiefer, Noemí Mercado, Nova DasSarma, Robert Lasenby, Robin Larson, Sam Ringer, Scott Johnston, Shauna Kravec, Sheer El Showk, Stanislav Fort, Tamera Lanham, Timothy Telleen-Lawton, Tom Conerly, Tom Henighan, Tristan Hume, Samuel R. Bowman, Zac Hatfield-Dodds, Ben Mann, Dario Amodei, Nicholas Joseph, Sam McCandlish, Tom Brown, and Jared Kaplan. 2022. Constitutional AI: Harmlessness from AI Feedback. CoRR abs/2212.08073 (2022). https://doi.org/10.48550/arXiv.2212.08073
[10]
Vevake Balaraman and Bernardo Magnini. 2020. Investigating Proactivity in Task-Oriented Dialogues. In CLiC-it, Vol. 2769.
[11]
Vevake Balaraman and Bernardo Magnini. 2020. Proactive systems and influenceable users: Simulating proactivity in task-oriented dialogues. In SEMDIAL.
[12]
Vevake Balaraman, Seyedmostafa Sheikhalishahi, and Bernardo Magnini. 2021. Recent Neural Methods on Dialogue State Tracking for Task-Oriented Dialogue Systems: A Survey. In SIGdial. 239–251.
[13]
Nolwenn Bernard and Krisztian Balog. 2023. MG-ShopDial: A Multi-Goal Conversational Dataset for e-Commerce. In SIGIR 2023. 2775–2785.
[14]
Keping Bi, Qingyao Ai, and W. Bruce Croft. 2021. Asking Clarifying Questions Based on Negative Feedback in Conversational Search. In ICTIR. 157–166.
[15]
Giovanni Maria Biancofiore, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, and Fedelucio Narducci. 2024. Interactive Question Answering Systems: Literature Review. ACM Comput. Surv. 56, 9 (2024), 239:1–239:38.
[16]
Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, Asli Celikyilmaz, and Yejin Choi. 2019. COMET: Commonsense Transformers for Automatic Knowledge Graph Construction. In ACL. 4762–4779.
[17]
Nicholas Botzer, Shawn Gu, and Tim Weninger. 2022. Analysis of Moral Judgment on Reddit. IEEE Transactions on Computational Social Systems (2022).
[18]
Pavel Braslavski, Denis Savenkov, Eugene Agichtein, and Alina Dubatovka. 2017. What Do You Mean Exactly?: Analyzing Clarification Questions in CQA. In CHIIR. 345–348.
[19]
Pawel Budzianowski, Tsung-Hsien Wen, Bo-Hsiang Tseng, Iñigo Casanueva, Stefan Ultes, Osman Ramadan, and Milica Gasic. 2018. MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling. In EMNLP.
[20]
Kushal Chawla, Gale M. Lucas, Jonathan May, and Jonathan Gratch. 2022. Opponent Modeling in Negotiation Dialogues by Related Data Adaptation. In Findings of ACL: NAACL. 661–674.
[21]
Hongshen Chen, Xiaorui Liu, Dawei Yin, and Jiliang Tang. 2017. A Survey on Dialogue Systems: Recent Advances and New Frontiers. SIGKDD Explor. (2017).
[22]
Maximillian Chen, Alexandros Papangelis, Chenyang Tao, Seokhwan Kim, Andy Rosenbaum, Yang Liu, Zhou Yu, and Dilek Hakkani-Tur. 2023. PLACES: Prompting Language Models for Social Conversation Synthesis. In Findings of ACL: EACL 2023. 814–838.
[23]
Maximillian Chen, Weiyan Shi, Feifan Yan, Ryan Hou, Jingwen Zhang, Saurav Sahay, and Zhou Yu. 2022. Seamlessly Integrating Factual Information and Social Content with Persuasive Dialogue. In AACL/IJCNLP.
[24]
Maximillian Chen, Ruoxi Sun, Sercan Ö Arık, and Tomas Pfister. 2024. Learning to Clarify: Multi-turn Conversations with Action-Based Contrastive Self-Training. arXiv preprint arXiv:2406.00222 (2024).
[25]
Maximillian Chen, Xiao Yu, Weiyan Shi, Urvi Awasthi, and Zhou Yu. 2023. Controllable Mixed-Initiative Dialogue Generation through Prompting. In ACL 2023. 951–966.
[26]
Nuo Chen, Yang Deng, and Jia Li. 2024. The Oscars of AI Theater: A Survey on Role-Playing with Language Models. CoRR abs/2407.11484 (2024).
[27]
Yue Chen, Chen Huang, Yang Deng, Wenqiang Lei, Dingnan Jin, Jia Liu, and Tat-Seng Chua. 2024. STYLE: Improving Domain Transferability of Asking Clarification Questions in Large Language Model Powered Conversational Agents. In Findings of the Association for Computational Linguistics, ACL 2024. Association for Computational Linguistics, 10633–10649.
[28]
Zhi Chen, Lu Chen, Bei Chen, Libo Qin, Yuncong Liu, Su Zhu, Jian-Guang Lou, and Kai Yu. 2022. UniDU: Towards A Unified Generative Dialogue Understanding Framework. In SIGDIAL.
[29]
Zhiyu Chen, Bing Liu, Seungwhan Moon, Chinnadhurai Sankar, Paul A. Crook, and William Yang Wang. 2022. KETOD: Knowledge-Enriched Task-Oriented Dialogue. In Findings of ACL: NAACL.
[30]
Yi Cheng, Wenge Liu, Wenjie Li, Jiashuo Wang, Ruihui Zhao, Bang Liu, Xiaodan Liang, and Yefeng Zheng. 2022. Improving Multi-turn Emotional Support Dialogue Generation with Lookahead Strategy Planning. CoRR abs/2210.04242 (2022).
[31]
Yi Cheng, Wenge Liu, Jian Wang, Chak Tou Leong, Yi Ouyang, Wenjie Li, Xian Wu, and Yefeng Zheng. 2024. Cooper: Coordinating Specialized Agents towards a Complex Dialogue Goal. In Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024. AAAI Press, 17853–17861.
[32]
Ssu Chiu, Maolin Li, Yen-Ting Lin, and Yun-Nung Chen. 2022. SalesBot: Transitioning from Chit-Chat to Task-Oriented Dialogues. In ACL.
[33]
Eunsol Choi, He He, Mohit Iyyer, Mark Yatskar, Wen-tau Yih, Yejin Choi, Percy Liang, and Luke Zettlemoyer. 2018. QuAC: Question Answering in Context. In EMNLP. 2174–2184.
[34]
Philipp Christmann, Rishiraj Saha Roy, and Gerhard Weikum. 2022. Conversational Question Answering on Heterogeneous Sources. In SIGIR. 144–154.
[35]
Jeffrey Dalton, Chenyan Xiong, Vaibhav Kumar, and Jamie Callan. 2020. CAsT-19: A Dataset for Conversational Information Seeking. In SIGIR. 1985–1988.
[36]
Huy Dao, Yang Deng, Khanh-Huyen Bui, Dung D. Le, and Lizi Liao. 2024. Experience as Source for Anticipation and Planning: Experiential Policy Learning for Target-driven Recommendation Dialogues. In Findings of the Association for Computational Linguistics: EMNLP 2024. Association for Computational Linguistics, 14179–14198.
[37]
Yang Deng, Wenqiang Lei, Minlie Huang, and Tat-Seng Chua. 2023. Goal Awareness for Conversational AI: Proactivity, Non-collaborativity, and Beyond. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts, ACL 2023. 1–10.
[38]
Yang Deng, Wenqiang Lei, Wai Lam, and Tat-Seng Chua. 2023. A Survey on Proactive Dialogue Systems: Problems, Methods, and Prospects. In IJCAI 2023. 6583–6591.
[39]
Yang Deng, Wenqiang Lei, Wenxuan Zhang, Wai Lam, and Tat-Seng Chua. 2022. PACIFIC: Towards Proactive Conversational Question Answering over Tabular and Textual Data in Finance. In EMNLP.
[40]
Yang Deng, Shuaiyi Li, and Wai Lam. 2023. Learning to Ask Clarification Questions with Spatial Reasoning. In SIGIR 2023. 2113–2117.
[41]
Yang Deng, Yaliang Li, Bolin Ding, and Wai Lam. 2022. Leveraging Long Short-Term User Preference in Conversational Recommendation Via Multi-Agent Reinforcement Learning. IEEE Transactions on Knowledge and Data Engineering (2022).
[42]
Yang Deng, Yaliang Li, Fei Sun, Bolin Ding, and Wai Lam. 2021. Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning. In SIGIR.
[43]
Yang Deng, Lizi Liao, Liang Chen, Hongru Wang, Wenqiang Lei, and Tat-Seng Chua. 2023. Prompting and Evaluating Large Language Models for Proactive Dialogues: Clarification, Target-guided, and Non-collaboration. In Findings of the Association for Computational Linguistics: EMNLP 2023. 10602–10621.
[44]
Yang Deng, Lizi Liao, Zhonghua Zheng, Grace Hui Yang, and Tat-Seng Chua. 2024. Towards Human-centered Proactive Conversational Agents. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, Washington DC, USA, July 14-18, 2024. ACM, 807–818.
[45]
Yang Deng, Wenxuan Zhang, Wai Lam, Hong Cheng, and Helen Meng. 2022. User Satisfaction Estimation with Sequential Dialogue Act Modeling in Goal-oriented Conversational Systems. In WWW 2022. 2998–3008.
[46]
Yang Deng, Wenxuan Zhang, Wai Lam, See-Kiong Ng, and Tat-Seng Chua. 2024. Plug-and-Play Policy Planner for Large Language Model Powered Dialogue Agents. In The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024. OpenReview.net.
[47]
Yang Deng, Wenxuan Zhang, Weiwen Xu, Wenqiang Lei, Tat-Seng Chua, and Wai Lam. 2022. A Unified Multi-task Learning Framework for Multi-goal Conversational Recommender Systems. TOIS (2022).
[48]
Yang Deng, Wenxuan Zhang, Yifei Yuan, and Wai Lam. 2023. Knowledge-enhanced Mixed-initiative Dialogue System for Emotional Support Conversations. In ACL 2023. 4079–4095.
[49]
Jan Deriu, Álvaro Rodrigo, Arantxa Otegi, Guillermo Echegoyen, Sophie Rosset, Eneko Agirre, and Mark Cieliebak. 2021. Survey on evaluation methods for dialogue systems. Artif. Intell. Rev. 54, 1 (2021), 755–810.
[50]
Emily Dinan, Samuel Humeau, Bharath Chintagunta, and Jason Weston. 2019. Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack. In EMNLP-IJCNLP.
[51]
Emily Dinan, Varvara Logacheva, Valentin Malykh, Alexander H. Miller, Kurt Shuster, Jack Urbanek, Douwe Kiela, Arthur Szlam, Iulian Serban, Ryan Lowe, Shrimai Prabhumoye, Alan W. Black, Alexander I. Rudnicky, Jason D. Williams, Joelle Pineau, Mikhail S. Burtsev, and Jason Weston. 2019. The Second Conversational Intelligence Challenge (ConvAI2). CoRR abs/1902.00098 (2019).
[52]
Dheeru Dua, Shivanshu Gupta, Sameer Singh, and Matt Gardner. 2022. Successive Prompting for Decomposing Complex Questions. In EMNLP. 1251–1265.
[53]
Ritam Dutt, Sayan Sinha, Rishabh Joshi, Surya Shekhar Chakraborty, Meredith Riggs, Xinru Yan, Haogang Bao, and Carolyn P. Rosé. 2021. ResPer: Computationally Modelling Resisting Strategies in Persuasive Conversations. In EACL.
[54]
Nouha Dziri, Sivan Milton, Mo Yu, Osmar R. Zaïane, and Siva Reddy. 2022. On the Origin of Hallucinations in Conversational Models: Is it the Datasets or the Models?. In NAACL 2022. 5271–5285.
[55]
Ahmed Elgohary, Denis Peskov, and Jordan L. Boyd-Graber. 2019. Can You Unpack That? Learning to Rewrite Questions-in-Context. In EMNLP-IJCNLP. 5917–5923.
[56]
Jiabao Fang, Shen Gao, Pengjie Ren, Xiuying Chen, Suzan Verberne, and Zhaochun Ren. 2024. A Multi-Agent Conversational Recommender System. CoRR abs/2402.01135 (2024).
[57]
Yue Feng, Gerasimos Lampouras, and Ignacio Iacobacci. 2022. Topic-Aware Response Generation in Task-Oriented Dialogue with Unstructured Knowledge Access. In Findings of ACL: EMNLP. 7199–7211.
[58]
Yue Feng, Shuchang Liu, Zhenghai Xue, Qingpeng Cai, Lantao Hu, Peng Jiang, Kun Gai, and Fei Sun. 2023. A Large Language Model Enhanced Conversational Recommender System. CoRR abs/2308.06212 (2023).
[59]
Yue Feng, Hossein A. Rahmani, Aldo Lipani, and Emine Yilmaz. 2023. Towards Asking Clarification Questions for Information Seeking on Task-Oriented Dialogues. CoRR abs/2305.13690 (2023).
[60]
M. Forbes, J. Hwang, V. Shwartz, M. Sap, and Y. Choi. 2020. Social Chemistry 101: Learning to Reason about Social and Moral Norms. In EMNLP.
[61]
Yao Fu, Hao Peng, Tushar Khot, and Mirella Lapata. 2023. Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback. CoRR abs/2305.10142 (2023). https://doi.org/10.48550/arXiv.2305.10142
[62]
Chang Gao and Wai Lam. 2022. Search Clarification Selection via Query-Intent-Clarification Graph Attention. In ECIR, Vol. 13185. 230–243.
[63]
Jianfeng Gao, Michel Galley, and Lihong Li. 2019. Neural Approaches to Conversational AI. Found. Trends Inf. Retr. 13, 2-3 (2019), 127–298.
[64]
Jun Gao, Yuhan Liu, Haolin Deng, Wei Wang, Yu Cao, Jiachen Du, and Ruifeng Xu. 2021. Improving Empathetic Response Generation by Recognizing Emotion Cause in Conversations. In Findings of ACL: EMNLP. 807–819.
[65]
Jianfeng Gao, Chenyan Xiong, Paul Bennett, and Nick Craswell. 2022. Neural Approaches to Conversational Information Retrieval. CoRR abs/2201.05176 (2022).
[66]
Yifan Gao, Chien-Sheng Wu, Shafiq R. Joty, Caiming Xiong, Richard Socher, Irwin King, Michael R. Lyu, and Steven C. H. Hoi. 2020. Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading. In ACL. 935–945.
[67]
Yifan Gao, Chien-Sheng Wu, Jingjing Li, Shafiq R. Joty, Steven C. H. Hoi, Caiming Xiong, Irwin King, and Michael R. Lyu. 2020. Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine Reading. In EMNLP. 2439–2449.
[68]
Karthik Gopalakrishnan, Behnam Hedayatnia, Qinglang Chen, Anna Gottardi, Sanjeev Kwatra, Anu Venkatesh, Raefer Gabriel, and Dilek Hakkani-Tür. 2019. Topical-Chat: Towards Knowledge-Grounded Open-Domain Conversations. In Interspeech.
[69]
Adam M Grant and Susan J Ashford. 2008. The dynamics of proactivity at work. Research in organizational behavior (2008).
[70]
Meiqi Guo, Mingda Zhang, Siva Reddy, and Malihe Alikhani. 2021. Abg-CoQA: Clarifying Ambiguity in Conversational Question Answering. In AKBC.
[71]
Prakhar Gupta, Harsh Jhamtani, and Jeffrey P. Bigham. 2022. Target-Guided Dialogue Response Generation Using Commonsense and Data Augmentation. In Findings of ACL: NAACL.
[72]
He He, Derek Chen, Anusha Balakrishnan, and Percy Liang. 2018. Decoupling Strategy and Generation in Negotiation Dialogues. In EMNLP.
[73]
Tao He, Lizi Liao, Yixin Cao, Yuanxing Liu, Ming Liu, Zerui Chen, and Bing Qin. 2024. Planning Like Human: A Dual-process Framework for Dialogue Planning. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2024, Bangkok, Thailand, August 11-16, 2024. Association for Computational Linguistics, 4768–4791.
[74]
Clara E Hill. 2009. Helping skills: Facilitating, exploration, insight, and action. (2009).
[75]
Ehsan Hosseini-Asl, Bryan McCann, Chien-Sheng Wu, Semih Yavuz, and Richard Socher. 2020. A Simple Language Model for Task-Oriented Dialogue. In NeurIPS.
[76]
Zhiyuan Hu, Yue Feng, Anh Tuan Luu, Bryan Hooi, and Aldo Lipani. 2023. Unlocking the Potential of User Feedback: Leveraging Large Language Model as User Simulator to Enhance Dialogue System. CoRR abs/2306.09821 (2023).
[77]
Zhiqiang Hu, Roy Ka-Wei Lee, and Nancy F. Chen. 2022. Are Current Task-oriented Dialogue Systems Able to Satisfy Impolite Users? CoRR (2022).
[78]
Chen Huang, Peixin Qin, Yang Deng, Wenqiang Lei, Jiancheng Lv, and Tat-Seng Chua. 2024. Concept - An Evaluation Protocol on Conversational Recommender Systems with System-centric and User-centric Factors. CoRR abs/2404.03304 (2024).
[79]
Hsin-Yuan Huang, Eunsol Choi, and Wen-tau Yih. 2019. FlowQA: Grasping Flow in History for Conversational Machine Comprehension. In ICLR.
[80]
Minlie Huang, Xiaoyan Zhu, and Jianfeng Gao. 2020. Challenges in Building Intelligent Open-domain Dialog Systems. ACM Trans. Inf. Syst. (2020).
[81]
Wenlong Huang, Pieter Abbeel, Deepak Pathak, and Igor Mordatch. 2022. Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents. In International Conference on Machine Learning, ICML, Vol. 162. 9118–9147.
[82]
Andrea Iovine, Fedelucio Narducci, and Giovanni Semeraro. 2020. Conversational Recommender Systems and natural language:: A study through the ConveRSE framework. Decis. Support Syst. 131 (2020), 113250.
[83]
Dietmar Jannach. 2023. Evaluating conversational recommender systems. Artif. Intell. Rev. 56, 3 (2023), 2365–2400.
[84]
Dietmar Jannach, Ahtsham Manzoor, Wanling Cai, and Li Chen. 2022. A Survey on Conversational Recommender Systems. ACM Comput. Surv. 54, 5 (2022), 105:1–105:36.
[85]
Rishabh Joshi, Vidhisha Balachandran, Shikhar Vashishth, Alan W. Black, and Yulia Tsvetkov. 2021. DialoGraph: Incorporating Interpretable Strategy-Graph Networks into Negotiation Dialogues. In ICLR.
[86]
Dongyeop Kang, Anusha Balakrishnan, Pararth Shah, Paul A. Crook, Y-Lan Boureau, and Jason Weston. 2019. Recommendation as a Communication Game: Self-Supervised Bot-Play for Goal-oriented Dialogue. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, EMNLP-IJCNLP 2019, Hong Kong, China, November 3-7, 2019. Association for Computational Linguistics, 1951–1961.
[87]
Kimiya Keyvan and Jimmy Xiangji Huang. 2023. How to Approach Ambiguous Queries in Conversational Search: A Survey of Techniques, Approaches, Tools, and Challenges. ACM Comput. Surv. 55, 6 (2023), 129:1–129:40.
[88]
Hyunwoo Kim, Jack Hessel, Liwei Jiang, Ximing Lu, Youngjae Yu, Pei Zhou, Ronan Le Bras, Malihe Alikhani, Gunhee Kim, Maarten Sap, and Yejin Choi. 2022. SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization. CoRR abs/2212.10465 (2022).
[89]
Hyunwoo Kim, Byeongchang Kim, and Gunhee Kim. 2021. Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes. In EMNLP. 2227–2240.
[90]
Heeseon Kim, Hyeongjun Yang, and Kyong-Ho Lee. 2023. Confident Action Decision via Hierarchical Policy Learning for Conversational Recommendation. In Proceedings of the ACM Web Conference 2023, WWW 2023. 1386–1395.
[91]
Hyunwoo Kim, Youngjae Yu, Liwei Jiang, Ximing Lu, Daniel Khashabi, Gunhee Kim, Yejin Choi, and Maarten Sap. 2022. ProsocialDialog: A Prosocial Backbone for Conversational Agents. In EMNLP.
[92]
Minju Kim, Chaehyeong Kim, Yongho Song, Seung-won Hwang, and Jinyoung Yeo. 2022. BotsTalk: Machine-sourced Framework for Automatic Curation of Large-scale Multi-skill Dialogue Datasets. In EMNLP 2022. 5149–5170.
[93]
Yosuke Kishinami, Reina Akama, Shiki Sato, Ryoko Tokuhisa, Jun Suzuki, and Kentaro Inui. 2022. Target-Guided Open-Domain Conversation Planning. In COLING.
[94]
Chuyi Kong, Yaxin Fan, Xiang Wan, Feng Jiang, and Benyou Wang. 2023. Large Language Model as a User Simulator. CoRR abs/2308.11534 (2023).
[95]
Satwik Kottur, Seungwhan Moon, Alborz Geramifard, and Babak Damavandi. 2021. SIMMC 2.0: A Task-oriented Dialog Dataset for Immersive Multimodal Conversations. In EMNLP. 4903–4912.
[96]
Chia-Hsuan Lee, Hao Cheng, and Mari Ostendorf. 2021. Dialogue State Tracking with a Language Model using Schema-Driven Prompting. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021. 4937–4949. https://doi.org/10.18653/v1/2021.emnlp-main.404
[97]
Gibbeum Lee, Volker Hartmann, Jongho Park, Dimitris Papailiopoulos, and Kangwook Lee. 2023. Prompted LLMs as Chatbot Modules for Long Open-domain Conversation. CoRR abs/2305.04533 (2023). https://doi.org/10.48550/arXiv.2305.04533
[98]
Wenqiang Lei, Xiangnan He, Yisong Miao, Qingyun Wu, Richang Hong, Min-Yen Kan, and Tat-Seng Chua. 2020. Estimation-Action-Reflection: Towards Deep Interaction Between Conversational and Recommender Systems. In WSDM.
[99]
Wenqiang Lei, Xisen Jin, Min-Yen Kan, Zhaochun Ren, Xiangnan He, and Dawei Yin. 2018. Sequicity: Simplifying Task-oriented Dialogue Systems with Single Sequence-to-Sequence Architectures. In ACL.
[100]
Wenqiang Lei, Yao Zhang, Feifan Song, Hongru Liang, Jiaxin Mao, J. Lv, Z. Yang, and Tat-Seng Chua. 2022. Interacting with Non-Cooperative User: A New Paradigm for Proactive Dialogue Policy. In SIGIR.
[101]
Chuang Li, Yang Deng, Hengchang Hu, Min-Yen Kan, and Haizhou Li. 2024. Incorporating External Knowledge and Goal Guidance for LLM-based Conversational Recommender Systems. CoRR abs/2405.01868 (2024).
[102]
Haoran Li, Yangqiu Song, and Lixin Fan. 2022. You Don’t Know My Favorite Color: Preventing Dialogue Representations from Revealing Speakers’ Private Personas. In NAACL.
[103]
Miaoran Li, Baolin Peng, Jianfeng Gao, and Zhu Zhang. 2022. OPERA: Harmonizing Task-Oriented Dialogs and Information Seeking Experience. CoRR (2022).
[104]
Raymond Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, and Chris Pal. 2018. Towards Deep Conversational Recommendations. In NeurIPS.
[105]
Shuokai Li, Ruobing Xie, Yongchun Zhu, Xiang Ao, Fuzhen Zhuang, and Qing He. 2022. User-Centric Conversational Recommendation with Multi-Aspect User Modeling. In SIGIR. 223–233.
[106]
Siheng Li, Yichun Yin, Cheng Yang, Wangjie Jiang, Yiwei Li, Zesen Cheng, Lifeng Shang, Xin Jiang, Qun Liu, and Yujiu Yang. [n.d.]. NewsDialogues: Towards Proactive News Grounded Conversation. In Findings of ACL: ACL 2023, pages = 3634–3649, year = 2023,.
[107]
Xiang Li, Lili Mou, Rui Yan, and Ming Zhang. 2016. StalemateBreaker: A Proactive Content-Introducing Approach to Automatic Human-Computer Conversation. In IJCAI.
[108]
Yongqi Li, Wenjie Li, and Liqiang Nie. 2022. MMCoQA: Conversational Question Answering over Text, Tables, and Images. In ACL. 4220–4231.
[109]
Yu Li, Kun Qian, Weiyan Shi, and Zhou Yu. 2020. End-to-End Trainable Non-Collaborative Dialog System. In AAAI.
[110]
Yanran Li, Hui Su, Xiaoyu Shen, Wenjie Li, Ziqiang Cao, and Shuzi Niu. 2017. DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset. In IJCNLP.
[111]
Yanyang Li, Jianqiao Zhao, Michael R. Lyu, and Liwei Wang. 2022. Eliciting Knowledge from Large Pre-Trained Models for Unsupervised Knowledge-Grounded Conversation. In EMNLP 2022. 10551–10564.
[112]
Zekun Li, Baolin Peng, Pengcheng He, Michel Galley, Jianfeng Gao, and Xifeng Yan. 2023. Guiding Large Language Models via Directional Stimulus Prompting. CoRR abs/2302.11520 (2023).
[113]
Lizi Liao, Le Hong Long, Yunshan Ma, Wenqiang Lei, and Tat-Seng Chua. 2021. Dialogue state tracking with incremental reasoning. TACL 9 (2021), 557–569.
[114]
Lizi Liao, Grace Hui Yang, and Chirag Shah. 2023. Proactive Conversational Agents. In Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, WSDM 2023. 1244–1247.
[115]
Lizi Liao, Grace Hui Yang, and Chirag Shah. 2023. Proactive Conversational Agents in the Post-ChatGPT World. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023. 3452–3455.
[116]
Allen Lin, Ziwei Zhu, Jianling Wang, and James Caverlee. 2023. Enhancing User Personalization in Conversational Recommenders. In Proceedings of the ACM Web Conference 2023, WWW 2023. 770–778.
[117]
Jiawei Liu, Kaisong Song, Yangyang Kang, Guoxiu He, Zhuoren Jiang, Changlong Sun, Wei Lu, and Xiaozhong Liu. 2021. A Role-Selected Sharing Network for Joint Machine-Human Chatting Handoff and Service Satisfaction Analysis. In EMNLP. 9731–9741.
[118]
Siyang Liu, Chujie Zheng, Orianna Demasi, Sahand Sabour, Yu Li, Zhou Yu, Yong Jiang, and Minlie Huang. 2021. Towards Emotional Support Dialog Systems. In ACL/IJCNLP.
[119]
Yinhong Liu, Yimai Fang, David Vandyke, and Nigel Collier. 2024. TOAD: Task-Oriented Automatic Dialogs with Diverse Response Styles. CoRR abs/2402.10137 (2024).
[120]
Ye Liu, Stefan Ultes, Wolfgang Minker, and Wolfgang Maier. 2023. System-Initiated Transitions from Chit-Chat to Task-Oriented Dialogues with Transition Info Extractor and Transition Sentence Generator. In INLG 2023.
[121]
Ye Liu, Stefan Ultes, Wolfgang Minker, and Wolfgang Maier. 2023. Unified Conversational Models with System-Initiated Transitions between Chit-Chat and Task-Oriented Dialogues. In CUI 2023. 33:1–33:9. https://doi.org/10.1145/3571884.3597125
[122]
Zihan Liu, Mostofa Patwary, Ryan Prenger, Shrimai Prabhumoye, Wei Ping, Mohammad Shoeybi, and Bryan Catanzaro. 2022. Multi-Stage Prompting for Knowledgeable Dialogue Generation. In Findings of the Association for Computational Linguistics: ACL 2022. 1317–1337. https://doi.org/10.18653/v1/2022.findings-acl.104
[123]
Zeming Liu, Haifeng Wang, Zheng-Yu Niu, Hua Wu, Wanxiang Che, and Ting Liu. 2020. Towards Conversational Recommendation over Multi-Type Dialogs. In ACL.
[124]
Zeming Liu, Jun Xu, Zeyang Lei, Haifeng Wang, Zheng-Yu Niu, and Hua Wu. 2022. Where to Go for the Holidays: Towards Mixed-Type Dialogs for Clarification of User Goals. In ACL.
[125]
Zeming Liu, Ding Zhou, Hao Liu, Haifeng Wang, Zheng-Yu Niu, Hua Wu, Wanxiang Che, Ting Liu, and Hui Xiong. 2023. Graph-Grounded Goal Planning for Conversational Recommendation. IEEE Trans. Knowl. Data Eng. 35, 5 (2023), 4923–4939.
[126]
Jakub Macina, Nico Daheim, Sankalan Pal Chowdhury, Tanmay Sinha, Manu Kapur, Iryna Gurevych, and Mrinmaya Sachan. 2023. MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems. CoRR abs/2305.14536 (2023).
[127]
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Sean Welleck, Bodhisattwa Prasad Majumder, Shashank Gupta, Amir Yazdanbakhsh, and Peter Clark. 2023. Self-Refine: Iterative Refinement with Self-Feedback. CoRR abs/2303.17651 (2023). https://doi.org/10.48550/arXiv.2303.17651
[128]
Ganeshan Malhotra, Abdul Waheed, Aseem Srivastava, Md. Shad Akhtar, and Tanmoy Chakraborty. 2022. Speaker and Time-aware Joint Contextual Learning for Dialogue-act Classification in Counselling Conversations. In WSDM.
[129]
Nicholas Meade, Spandana Gella, Devamanyu Hazarika, Prakhar Gupta, Di Jin, Siva Reddy, Yang Liu, and Dilek Hakkani-Tur. 2023. Using In-Context Learning to Improve Dialogue Safety. In Findings of the Association for Computational Linguistics: EMNLP 2023, Singapore, December 6-10, 2023. Association for Computational Linguistics, 11882–11910.
[130]
Fei Mi, Yasheng Wang, and Yitong Li. 2022. CINS: Comprehensive Instruction for Few-Shot Learning in Task-Oriented Dialog Systems. In Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI 2022. 11076–11084. https://ojs.aaai.org/index.php/AAAI/article/view/21356
[131]
Sewon Min, Victor Zhong, Luke Zettlemoyer, and Hannaneh Hajishirzi. 2019. Multi-hop Reading Comprehension through Question Decomposition and Rescoring. In ACL. 6097–6109.
[132]
Kshitij Mishra, Azlaan Mustafa Samad, Palak Totala, and Asif Ekbal. 2022. PEPDS: A Polite and Empathetic Persuasive Dialogue System for Charity Donation. In COLING.
[133]
Shrestha Mohanty, Negar Arabzadeh, Milagro Teruel, Yuxuan Sun, Artem Zholus, Alexey Skrynnik, Mikhail S. Burtsev, Kavya Srinet, Aleksandr Panov, Arthur Szlam, Marc-Alexandre Côté, and Julia Kiseleva. 2022. Collecting Interactive Multi-modal Datasets for Grounded Language Understanding. CoRR abs/2211.06552 (2022).
[134]
Seungwhan Moon, Pararth Shah, Anuj Kumar, and Rajen Subba. 2019. OpenDialKG: Explainable Conversational Reasoning with Attention-based Walks over Knowledge Graphs. In ACL. 845–854.
[135]
Theresa B Moyers, Tim Martin, Jennifer K Manuel, Stacey ML Hendrickson, and William R Miller. 2005. Assessing competence in the use of motivational interviewing. Journal of substance abuse treatment 28, 1 (2005), 19–26.
[136]
Gee Wah Ng and Wang Chi Leung. 2020. Strong Artificial Intelligence and Consciousness. J. Artif. Intell. Conscious. (2020).
[137]
Jinjie Ni, Tom Young, Vlad Pandelea, Fuzhao Xue, Vinay Adiga, and Erik Cambria. 2021. Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Survey. CoRR abs/2105.04387 (2021).
[138]
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul F. Christiano, Jan Leike, and Ryan Lowe. 2022. Training language models to follow instructions with human feedback. CoRR abs/2203.02155 (2022).
[139]
Siru Ouyang, Zhuosheng Zhang, and Hai Zhao. 2021. Dialogue Graph Modeling for Conversational Machine Reading. In Findings of ACL: ACL/IJCNLP 2021, Vol. ACL/IJCNLP. 3158–3169.
[140]
Paul Owoicho, Ivan Sekulic, Mohammad Aliannejadi, Jeffrey Dalton, and Fabio Crestani. 2023. Exploiting Simulated User Feedback for Conversational Search: Ranking, Rewriting, and Beyond. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023. ACM, 632–642.
[141]
Baolin Peng, Chunyuan Li, Jinchao Li, Shahin Shayandeh, Lars Liden, and Jianfeng Gao. 2021. SOLOIST: Building Task Bots at Scale with Transfer Learning and Machine Teaching. Trans. Assoc. Comput. Linguistics 9 (2021), 907–824.
[142]
Wei Peng, Yue Hu, Luxi Xing, Yuqiang Xie, Yajing Sun, and Yunpeng Li. 2022. Control Globally, Understand Locally: A Global-to-Local Hierarchical Graph Network for Emotional Support Conversation. CoRR abs/2204.12749 (2022).
[143]
Verónica Pérez-Rosas, Rada Mihalcea, Kenneth Resnicow, Satinder Singh, and Lawrence C. An. 2016. Building a Motivational Interviewing Dataset. In CLPsych@NAACL-HLT. 42–51.
[144]
Verónica Pérez-Rosas, Rada Mihalcea, Kenneth Resnicow, Satinder Singh, Lawrence C. An, Kathy J. Goggin, and Delwyn Catley. 2017. Predicting Counselor Behaviors in Motivational Interviewing Encounters. In EACL. 1128–1137.
[145]
Soujanya Poria, Navonil Majumder, Devamanyu Hazarika, Deepanway Ghosal, Rishabh Bhardwaj, Samson Yu Bai Jian, Pengfei Hong, Romila Ghosh, Abhinaba Roy, Niyati Chhaya, Alexander F. Gelbukh, and Rada Mihalcea. 2021. Recognizing Emotion Cause in Conversations. Cogn. Comput. 13, 5 (2021), 1317–1332.
[146]
Hongjin Qian and Zhicheng Dou. 2022. Explicit Query Rewriting for Conversational Dense Retrieval. In EMNLP. 4725–4737.
[147]
Kun Qian, Satwik Kottur, Ahmad Beirami, Shahin Shayandeh, Paul A. Crook, Alborz Geramifard, Zhou Yu, and Chinnadhurai Sankar. 2022. Database Search Results Disambiguation for Task-Oriented Dialog Systems. In NAACL. 1158–1173.
[148]
Jinghui Qin, Zheng Ye, Jianheng Tang, and Xiaodan Liang. 2020. Dynamic Knowledge Routing Network for Target-Guided Open-Domain Conversation. In AAAI.
[149]
Libo Qin, Wenbo Pan, Qiguang Chen, Lizi Liao, Zhou Yu, Yue Zhang, Wanxiang Che, and Min Li. 2023. End-to-end Task-oriented Dialogue: A Survey of Tasks, Methods, and Future Directions. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023. Association for Computational Linguistics, 5925–5941.
[150]
Peixin Qin, Chen Huang, Yang Deng, Wenqiang Lei, and Tat-Seng Chua. 2024. Beyond Persuasion: Towards Conversational Recommender System with Credible Explanations. In Findings of the Association for Computational Linguistics: EMNLP 2024. Association for Computational Linguistics, 4264–4282.
[151]
Chen Qu, Liu Yang, Minghui Qiu, Yongfeng Zhang, Cen Chen, W. Bruce Croft, and Mohit Iyyer. 2019. Attentive History Selection for Conversational Question Answering. In CIKM. 1391–1400.
[152]
Konigari Rachna, Saurabh Ramola, Vijay Vardhan Alluri, and Manish Shrivastava. 2021. Topic Shift Detection for Mixed Initiative Response. In SIGdial.
[153]
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019. Language models are unsupervised multitask learners. OpenAI blog 1, 8 (2019), 9.
[154]
Hossein A. Rahmani, Xi Wang, Yue Feng, Qiang Zhang, Emine Yilmaz, and Aldo Lipani. 2023. A Survey on Asking Clarification Questions Datasets in Conversational Systems. In ACL 2023. 2698–2716.
[155]
Sudha Rao and Hal Daumé III. 2018. Learning to Ask Good Questions: Ranking Clarification Questions using Neural Expected Value of Perfect Information. In ACL. 2737–2746.
[156]
Sudha Rao and Hal Daumé III. 2019. Answer-based Adversarial Training for Generating Clarification Questions. In NAACL-HLT. 143–155.
[157]
Hannah Rashkin, Eric Michael Smith, Margaret Li, and Y-Lan Boureau. 2019. Towards Empathetic Open-domain Conversation Models: A New Benchmark and Dataset. In ACL. 5370–5381.
[158]
Abhinav Rastogi, Xiaoxue Zang, Srinivas Sunkara, Raghav Gupta, and Pranav Khaitan. 2020. Towards Scalable Multi-Domain Conversational Agents: The Schema-Guided Dialogue Dataset. In AAAI. 8689–8696.
[159]
Siva Reddy, Danqi Chen, and Christopher D. Manning. 2019. CoQA: A Conversational Question Answering Challenge. Trans. Assoc. Comput. Linguistics (2019).
[160]
Pengjie Ren, Zhumin Chen, Zhaochun Ren, Evangelos Kanoulas, Christof Monz, and Maarten de Rijke. 2021. Conversations with Search Engines: SERP-based Conversational Response Generation. ACM Trans. Inf. Syst. 39, 4 (2021), 47:1–47:29.
[161]
Zhaochun Ren, Zhi Tian, Dongdong Li, Pengjie Ren, Liu Yang, Xin Xin, Huasheng Liang, Maarten de Rijke, and Zhumin Chen. 2022. Variational Reasoning about User Preferences for Conversational Recommendation. In SIGIR. 165–175.
[162]
Stephen Roller, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu, Myle Ott, Eric Michael Smith, Y-Lan Boureau, and Jason Weston. 2021. Recipes for Building an Open-Domain Chatbot. In EACL.
[163]
Marzieh Saeidi, Max Bartolo, Patrick S. H. Lewis, Sameer Singh, Tim Rocktäschel, Mike Sheldon, Guillaume Bouchard, and Sebastian Riedel. 2018. Interpretation of Natural Language Rules in Conversational Machine Reading. In EMNLP. 2087–2097.
[164]
Azlaan Mustafa Samad, Kshitij Mishra, Mauajama Firdaus, and Asif Ekbal. 2022. Empathetic Persuasion: Reinforcing Empathy and Persuasiveness in Dialogue Systems. In Findings of ACL: NAACL.
[165]
J Schulman, B Zoph, C Kim, J Hilton, J Menick, J Weng, JFC Uribe, L Fedus, L Metz, M Pokorny, et al. 2022. ChatGPT: Optimizing language models for dialogue.
[166]
John R Searle. 1992. The rediscovery of the mind. MIT press.
[167]
Ivan Sekulic, Mohammad Aliannejadi, and Fabio Crestani. 2022. Evaluating Mixed-initiative Conversational Search Systems via User Simulation. In WSDM.
[168]
Karin Sevegnani, David M. Howcroft, Ioannis Konstas, and Verena Rieser. 2021. OTTers: One-turn Topic Transitions for Open-Domain Dialogue. In ACL/IJCNLP 2021. 2492–2504.
[169]
Chenzhan Shang, Yupeng Hou, Wayne Xin Zhao, Yaliang Li, and Jing Zhang. 2023. Multi-grained Hypergraph Interest Modeling for Conversational Recommendation. CoRR abs/2305.04798 (2023).
[170]
Ashish Sharma, Adam S. Miner, David C. Atkins, and Tim Althoff. 2020. A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Support. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020, Online, November 16-20, 2020. Association for Computational Linguistics, 5263–5276.
[171]
Siqi Shen, Verónica Pérez-Rosas, Charles Welch, Soujanya Poria, and Rada Mihalcea. 2022. Knowledge Enhanced Reflection Generation for Counseling Dialogues. In ACL. 3096–3107.
[172]
Siqi Shen, Charles Welch, Rada Mihalcea, and Verónica Pérez-Rosas. 2020. Counseling-Style Reflection Generation Using Generative Pretrained Transformers with Augmented Context. In SIGdial. 10–20.
[173]
Weiyan Shi, Yu Li, Saurav Sahay, and Zhou Yu. 2021. Refine and Imitate: Reducing Repetition and Inconsistency in Persuasion Dialogues via Reinforcement Learning and Human Demonstration. In Findings of ACL: EMNLP.
[174]
Xiaoming Shi, Zeming Liu, Chuan Wang, Haitao Leng, Kui Xue, Xiaofan Zhang, and Shaoting Zhang. 2023. MidMed: Towards Mixed-Type Dialogues for Medical Consultation. In ACL 2023. 8145–8157.
[175]
Zhengxiang Shi, Yue Feng, and Aldo Lipani. 2022. Learning to Execute Actions or Ask Clarification Questions. In Findings of ACL: NAACL. 2060–2070.
[176]
Noah Shinn, Beck Labash, and Ashwin Gopinath. 2023. Reflexion: an autonomous agent with dynamic memory and self-reflection. CoRR abs/2303.11366 (2023). https://doi.org/10.48550/arXiv.2303.11366
[177]
Kurt Shuster, Mojtaba Komeili, Leonard Adolphs, Stephen Roller, Arthur Szlam, and Jason Weston. 2022. Language Models that Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completion. In Findings of the Association for Computational Linguistics: EMNLP 2022. 373–393. https://aclanthology.org/2022.findings-emnlp.27
[178]
Kurt Shuster, Jing Xu, Mojtaba Komeili, Da Ju, Eric Michael Smith, Stephen Roller, Megan Ung, Moya Chen, Kushal Arora, Joshua Lane, Morteza Behrooz, William Ngan, Spencer Poff, Naman Goyal, Arthur Szlam, Y-Lan Boureau, Melanie Kambadur, and Jason Weston. 2022. BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage. CoRR abs/2208.03188 (2022).
[179]
Eric Michael Smith, Mary Williamson, Kurt Shuster, Jason Weston, and Y-Lan Boureau. 2020. Can You Put it All Together: Evaluating Conversational Agents’ Ability to Blend Skills. In ACL. 2021–2030.
[180]
Aseem Srivastava, Ishan Pandey, Md. Shad Akhtar, and Tanmoy Chakraborty. 2023. Response-act Guided Reinforced Dialogue Generation for Mental Health Counseling. CoRR abs/2301.12729 (2023).
[181]
Yixuan Su, Lei Shu, Elman Mansimov, Arshit Gupta, Deng Cai, Yi-An Lai, and Yi Zhang. 2022. Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System. In ACL.
[182]
Hao Sun, Zhenru Lin, Chujie Zheng, Siyang Liu, and Minlie Huang. 2021. PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Support. In Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, Online Event, August 1-6, 2021 (Findings of ACL), Vol. ACL/IJCNLP 2021. Association for Computational Linguistics, 1489–1503.
[183]
Hao Sun, Guangxuan Xu, Jiawen Deng, Jiale Cheng, Chujie Zheng, Hao Zhou, Nanyun Peng, Xiaoyan Zhu, and Minlie Huang. 2022. On the Safety of Conversational Models: Taxonomy, Dataset, and Benchmark. In Findings of ACL: ACL 2022. 3906–3923.
[184]
Kai Sun, Seungwhan Moon, Paul A. Crook, Stephen Roller, Becka Silvert, Bing Liu, Zhiguang Wang, Honglei Liu, Eunjoon Cho, and Claire Cardie. 2021. Adding Chit-Chat to Enhance Task-Oriented Dialogues. In NAACL-HLT.
[185]
Jianheng Tang, Tiancheng Zhao, Chenyan Xiong, Xiaodan Liang, Eric Xing, and Zhiting Hu. 2019. Target-Guided Open-Domain Conversation. In ACL.
[186]
Zhiwen Tang and Grace Hui Yang. 2022. A Re-classification of Information Seeking Tasks and Their Computational Solutions. ACM Trans. Inf. Syst. 40, 4 (2022), 80:1–80:32.
[187]
Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, YaGuang Li, Hongrae Lee, Huaixiu Steven Zheng, Amin Ghafouri, Marcelo Menegali, Yanping Huang, Maxim Krikun, Dmitry Lepikhin, James Qin, Dehao Chen, Yuanzhong Xu, Zhifeng Chen, Adam Roberts, Maarten Bosma, Yanqi Zhou, Chung-Ching Chang, Igor Krivokon, Will Rusch, Marc Pickett, Kathleen S. Meier-Hellstern, Meredith Ringel Morris, Tulsee Doshi, Renelito Delos Santos, Toju Duke, Johnny Soraker, Ben Zevenbergen, Vinodkumar Prabhakaran, Mark Diaz, Ben Hutchinson, Kristen Olson, Alejandra Molina, Erin Hoffman-John, Josh Lee, Lora Aroyo, Ravi Rajakumar, Alena Butryna, Matthew Lamm, Viktoriya Kuzmina, Joe Fenton, Aaron Cohen, Rachel Bernstein, Ray Kurzweil, Blaise Aguera-Arcas, Claire Cui, Marian Croak, Ed H. Chi, and Quoc Le. 2022. LaMDA: Language Models for Dialog Applications. CoRR abs/2201.08239 (2022).
[188]
Quan Tu, Yanran Li, Jianwei Cui, Bin Wang, Ji-Rong Wen, and Rui Yan. 2022. MISC: A Mixed Strategy-Aware Model integrating COMET for Emotional Support Conversation. In ACL. 308–319.
[189]
Megan Ung, Jing Xu, and Y-Lan Boureau. 2022. SaFeRDialogues: Taking Feedback Gracefully after Conversational Safety Failures. In ACL. 6462–6481.
[190]
Svitlana Vakulenko, Shayne Longpre, Zhucheng Tu, and Raviteja Anantha. 2021. Question Rewriting for Conversational Question Answering. In WSDM. 355–363.
[191]
Nikos Voskarides, Dan Li, Pengjie Ren, Evangelos Kanoulas, and Maarten de Rijke. 2020. Query Resolution for Conversational Search with Limited Supervision. In SIGIR. 921–930.
[192]
Hongru Wang, Rui Wang, Fei Mi, Yang Deng, Zezhong Wang, Bin Liang, Ruifeng Xu, and Kam-Fai Wong. 2023. Cue-CoT: Chain-of-thought Prompting for Responding to In-depth Dialogue Questions with LLMs. In Findings of the Association for Computational Linguistics: EMNLP 2023, Singapore, December 6-10, 2023. Association for Computational Linguistics, 12047–12064.
[193]
Jian Wang, Yi Cheng, Dongding Lin, Chak Tou Leong, and Wenjie Li. 2023. Target-oriented Proactive Dialogue Systems with Personalization: Problem Formulation and Dataset Curation. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023, Singapore, December 6-10, 2023. Association for Computational Linguistics, 1132–1143.
[194]
Jian Wang, Chak Tou Leong, Jiashuo Wang, Dongding Lin, Wenjie Li, and Xiao-Yong Wei. 2024. Instruct Once, Chat Consistently in Multiple Rounds: An Efficient Tuning Framework for Dialogue. CoRR abs/2402.06967 (2024).
[195]
Jian Wang and Wenjie Li. 2021. Template-guided Clarifying Question Generation for Web Search Clarification. In CIKM. 3468–3472.
[196]
Jian Wang, Dongding Lin, and Wenjie Li. 2023. Dialogue Planning via Brownian Bridge Stochastic Process for Goal-directed Proactive Dialogue. In Findings of ACL 2023. 370–387.
[197]
Jiashuo Wang, Haozhao Wang, Shichao Sun, and Wenjie Li. 2023. Aligning Language Models with Human Preferences via a Bayesian Approach. In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023.
[198]
Lingzhi Wang, Huang Hu, Lei Sha, Can Xu, Daxin Jiang, and Kam-Fai Wong. 2022. RecInDial: A Unified Framework for Conversational Recommendation with Pretrained Language Models. In AACL/IJCNLP. 489–500.
[199]
Xuewei Wang, Weiyan Shi, Richard Kim, Yoojung Oh, Sijia Yang, Jingwen Zhang, and Zhou Yu. 2019. Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good. In ACL.
[200]
Xiaolei Wang, Xinyu Tang, Wayne Xin Zhao, Jingyuan Wang, and Ji-Rong Wen. 2023. Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models. CoRR abs/2305.13112 (2023).
[201]
Xiaolei Wang, Kun Zhou, Ji-Rong Wen, and Wayne Xin Zhao. 2022. Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learning. In KDD. 1929–1937.
[202]
Zhenduo Wang, Yuancheng Tu, Corby Rosset, Nick Craswell, Ming Wu, and Qingyao Ai. 2023. Zero-shot Clarifying Question Generation for Conversational Search. In Proceedings of the ACM Web Conference 2023, WWW 2023. 3288–3298.
[203]
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed H. Chi, Quoc Le, and Denny Zhou. 2022. Chain of Thought Prompting Elicits Reasoning in Large Language Models. CoRR abs/2201.11903 (2022).
[204]
Anuradha Welivita and Pearl Pu. 2022. HEAL: A Knowledge Graph for Distress Management Conversations. In AAAI.
[205]
Thomas Wolf, Victor Sanh, Julien Chaumond, and Clement Delangue. 2019. TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents. CoRR abs/1901.08149 (2019).
[206]
Chien-Sheng Wu, Steven C. H. Hoi, Richard Socher, and Caiming Xiong. 2020. TOD-BERT: Pre-trained Natural Language Understanding for Task-Oriented Dialogue. In EMNLP.
[207]
Qingyang Wu, Yichi Zhang, Yu Li, and Zhou Yu. 2021. Alternating Recurrent Dialog Model with Large-scale Pre-trained Language Models. In EACL.
[208]
Wenquan Wu, Zhen Guo, Xiangyang Zhou, Hua Wu, Xiyuan Zhang, Rongzhong Lian, and Haifeng Wang. 2019. Proactive Human-Machine Conversation with Explicit Conversation Goal. In ACL.
[209]
Zeqiu Wu, Ryu Parish, Hao Cheng, Sewon Min, Prithviraj Ammanabrolu, Mari Ostendorf, and Hannaneh Hajishirzi. 2022. INSCIT: Information-Seeking Conversations with Mixed-Initiative Interactions. CoRR abs/2207.00746 (2022).
[210]
Huiyuan Xie, Zhenghao Liu, Chenyan Xiong, Zhiyuan Liu, and Ann A. Copestake. 2021. TIAGE: A Benchmark for Topic-Shift Aware Dialog Modeling. In Findings of ACL: EMNLP.
[211]
Zhihui Xie, Tong Yu, Canzhe Zhao, and Shuai Li. 2021. Comparison-based Conversational Recommender System with Relative Bandit Feedback. In SIGIR. 1400–1409.
[212]
Canwen Xu, Daya Guo, Nan Duan, and Julian J. McAuley. 2023. Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat Data. CoRR abs/2304.01196 (2023).
[213]
Jing Xu, Da Ju, Margaret Li, Y. Boureau, Jason Weston, and Emily Dinan. 2021. Bot-Adversarial Dialogue for Safe Conversational Agents. In NAACL-HLT.
[214]
Jun Xu, Zeyang Lei, Haifeng Wang, Zheng-Yu Niu, Hua Wu, and Wanxiang Che. 2020. Enhancing Dialog Coherence with Event Graph Grounded Content Planning. In IJCAI.
[215]
Jingjing Xu, Yuechen Wang, Duyu Tang, Nan Duan, Pengcheng Yang, Qi Zeng, Ming Zhou, and Xu Sun. 2019. Asking Clarification Questions in Knowledge-Based Question Answering. In EMNLP-IJCNLP. 1618–1629.
[216]
Rui Yan, Juntao Li, and Zhou Yu. 2022. Deep Learning for Dialogue Systems: Chit-Chat and Beyond. Foundations and Trends in Information Retrieval 15, 5 (2022), 417–589.
[217]
Rui Yan and Dongyan Zhao. 2018. Smarter Response with Proactive Suggestion: A New Generative Neural Conversation Paradigm. In IJCAI.
[218]
Sitong Yan, Shengli Song, Jingyang Li, Shiqi Meng, and Guangneng Hu. 2023. TITAN: Task-oriented Dialogues with Mixed-Initiative Interactions. In IJCAI 2023. 5251–5259.
[219]
Runzhe Yang, Jingxiao Chen, and Karthik Narasimhan. 2021. Improving Dialog Systems for Negotiation with Personality Modeling. In ACL/IJCNLP.
[220]
Wei Yang, Luchen Tan, Chunwei Lu, Anqi Cui, Han Li, Xi Chen, Kun Xiong, Muzi Wang, Ming Li, Jian Pei, and Jimmy Lin. 2019. Detecting Customer Complaint Escalation with Recurrent Neural Networks and Manually-Engineered Features. In NAACL-HLT. 56–63.
[221]
Zhitong Yang, Bo Wang, Jinfeng Zhou, Yue Tan, Dongming Zhao, Kun Huang, Ruifang He, and Yuexian Hou. 2022. TopKG: Target-oriented Dialog via Global Planning on Knowledge Graph. In COLING.
[222]
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2022. ReAct: Synergizing Reasoning and Acting in Language Models. CoRR abs/2210.03629 (2022).
[223]
Weiran Yao, Shelby Heinecke, Juan Carlos Niebles, Zhiwei Liu, Yihao Feng, Le Xue, Rithesh Murthy, Zeyuan Chen, Jianguo Zhang, Devansh Arpit, Ran Xu, Phil Mui, Huan Wang, Caiming Xiong, and Silvio Savarese. 2023. Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization. arXiv:cs.CL/2308.02151
[224]
Chenchen Ye, Lizi Liao, Suyu Liu, and Tat-Seng Chua. 2022. Reflecting on experiences for response generation. In ACM Multimedia. 5265–5273.
[225]
Tom Young, Frank Xing, Vlad Pandelea, J. Ni, and E. Cambria. 2022. Fusing Task-Oriented and Open-Domain Dialogues in Conversational Agents. In AAAI.
[226]
Wenhao Yu, Dan Iter, Shuohang Wang, Yichong Xu, Mingxuan Ju, Soumya Sanyal, Chenguang Zhu, Michael Zeng, and Meng Jiang. 2022. Generate rather than Retrieve: Large Language Models are Strong Context Generators. CoRR abs/2209.10063 (2022).
[227]
Xiao Yu, Maximillian Chen, and Zhou Yu. 2023. Prompt-Based Monte-Carlo Tree Search for Goal-Oriented Dialogue Policy Planning. CoRR abs/2305.13660 (2023). https://doi.org/10.48550/arXiv.2305.13660
[228]
Hamed Zamani, Susan T. Dumais, Nick Craswell, Paul N. Bennett, and Gord Lueck. 2020. Generating Clarifying Questions for Information Retrieval. In WWW.
[229]
Hamed Zamani, Gord Lueck, Everest Chen, Rodolfo Quispe, Flint Luu, and Nick Craswell. 2020. MIMICS: A Large-Scale Data Collection for Search Clarification. In CIKM. 3189–3196.
[230]
Hamed Zamani, Johanne R. Trippas, Jeff Dalton, and Filip Radlinski. 2022. Conversational Information Seeking. CoRR (2022).
[231]
Haolan Zhan, Yufei Wang, Tao Feng, Yuncheng Hua, Suraj Sharma, Zhuang Li, Lizhen Qu, and Gholamreza Haffari. 2022. Let's Negotiate! A Survey of Negotiation Dialogue Systems. CoRR (2022).
[232]
Danyang Zhang, Lu Chen, Situo Zhang, Hongshen Xu, Zihan Zhao, and Kai Yu. 2023. Large Language Model Is Semi-Parametric Reinforcement Learning Agent. CoRR abs/2306.07929 (2023).
[233]
Jun Zhang, Yan Yang, Chencai Chen, Liang He, and Zhou Yu. 2021. KERS: A Knowledge-Enhanced Framework for Recommendation Dialog Systems with Multiple Subgoals. In Findings of ACL: EMNLP.
[234]
Qiang Zhang, Jason Naradowsky, and Yusuke Miyao. 2023. Ask an Expert: Leveraging Language Models to Improve Strategic Reasoning in Goal-Oriented Dialogue Models. In Findings of ACL: ACL 2023. 6665–6694.
[235]
Shuo Zhang and Krisztian Balog. 2020. Evaluating Conversational Recommender Systems via User Simulation. In KDD.
[236]
Saizheng Zhang, Emily Dinan, Jack Urbanek, Arthur Szlam, Douwe Kiela, and Jason Weston. 2018. Personalizing Dialogue Agents: I have a dog, do you have pets too?. In ACL.
[237]
Tong Zhang, Chen Huang, Yang Deng, Hongru Liang, Jia Liu, Zujie Wen, Wenqiang Lei, and Tat-Seng Chua. 2024. Strength Lies in Differences! Improving Strategy Planning for Non-collaborative Dialogues via Diversified User Simulation. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024, Miami, FL, USA, November 12-16, 2024. Association for Computational Linguistics, 424–444.
[238]
Xiaoying Zhang, Baolin Peng, Kun Li, Jingyan Zhou, and Helen Meng. 2023. SGP-TOD: Building Task Bots Effortlessly via Schema-Guided LLM Prompting. CoRR abs/2305.09067 (2023).
[239]
Yongfeng Zhang, Xu Chen, Qingyao Ai, Liu Yang, and W. Bruce Croft. 2018. Towards Conversational Search and Recommendation: System Ask, User Respond. In CIKM.
[240]
Yizhe Zhang, Siqi Sun, Michel Galley, Yen-Chun Chen, Chris Brockett, Xiang Gao, Jianfeng Gao, Jingjing Liu, and Bill Dolan. 2020. DIALOGPT: Large-Scale Generative Pre-training for Conversational Response Generation. In ACL.
[241]
Yiming Zhang, Lingfei Wu, Qi Shen, Yitong Pang, Zhihua Wei, F. Xu, B. Long, and J. Pei. 2022. Multiple Choice Questions based Multi-Interest Policy Learning for Conversational Recommendation. In WWW.
[242]
Chao Zhao, Spandana Gella, Seokhwan Kim, Di Jin, Devamanyu Hazarika, Alexandros Papangelis, Behnam Hedayatnia, Mahdi Namazifar, Yang Liu, and Dilek Hakkani-Tur. 2023. ”What do others think?”: Task-Oriented Conversational Modeling with Subjective Knowledge. CoRR abs/2305.12091 (2023).
[243]
Xinyan Zhao, Bin He, Yasheng Wang, Yitong Li, Fei Mi, Yajiao Liu, Xin Jiang, Qun Liu, and H. Chen. 2022. UniDS: A Unified Dialogue System for Chit-Chat and Task-oriented Dialogues. In DialDoc@ACL.
[244]
Xiangyu Zhao, Longbiao Wang, and Jianwu Dang. 2022. Improving Dialogue Generation via Proactively Querying Grounded Knowledge. In ICASSP. 6577–6581.
[245]
Ziliang Zhao, Zhicheng Dou, Jiaxin Mao, and Ji-Rong Wen. 2022. Generating Clarifying Questions with Web Search Results. In SIGIR. 234–244.
[246]
Chujie Zheng, Sahand Sabour, Jiaxin Wen, Zheng Zhang, and Minlie Huang. 2023. AugESC: Dialogue Augmentation with Large Language Models for Emotional Support Conversation. In Findings of ACL: ACL 2023. 1552–1568.
[247]
Zhonghua Zheng, Lizi Liao, Yang Deng, Ee-Peng Lim, Minlie Huang, and Liqiang Nie. 2024. Thoughts to Target: Enhance Planning for Target-driven Conversation. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024. Association for Computational Linguistics, 21108–21124.
[248]
Zhonghua Zheng, Lizi Liao, Yang Deng, Libo Qin, and Liqiang Nie. 2024. Self-chats from Large Language Models Make Small Emotional Support Chatbot Better. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2024, Bangkok, Thailand, August 11-16, 2024. Association for Computational Linguistics, 11325–11345.
[249]
Peixiang Zhong, Yong Liu, Hao Wang, and Chunyan Miao. 2021. Keyword-Guided Neural Conversational Model. In AAAI.
[250]
ShanShan Zhong, Jinghui Qin, Zhongzhan Huang, and Daifeng Li. 2022. CEM: Machine-Human Chatting Handoff via Causal-Enhance Module. In EMNLP 2022. 3242–3253.
[251]
Ben Zhou, Kyle Richardson, Xiaodong Yu, and Dan Roth. 2022. Learning to Decompose: Hypothetical Question Decomposition Based on Comparable Texts. In EMNLP. 2223–2235.
[252]
Hao Zhou, Minlie Huang, Tianyang Zhang, Xiaoyan Zhu, and Bing Liu. 2018. Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memory. In AAAI. 730–739.
[253]
Jinfeng Zhou, Zhuang Chen, Bo Wang, and Minlie Huang. 2023. Facilitating Multi-turn Emotional Support Conversation with Positive Emotion Elicitation: A Reinforcement Learning Approach. In ACL 2023. 1714–1729.
[254]
Kun Zhou, Yuanhang Zhou, Wayne Xin Zhao, Xiaoke Wang, and Ji-Rong Wen. 2020. Towards Topic-Guided Conversational Recommender System. In COLING.
[255]
Yiheng Zhou, He He, Alan W. Black, and Yulia Tsvetkov. 2019. A Dynamic Strategy Coach for Effective Negotiation. In SIGdial.
[256]
Yiheng Zhou, Yulia Tsvetkov, Alan W. Black, and Zhou Yu. 2020. Augmenting Non-Collaborative Dialog Systems with Explicit Semantic and Strategic Dialog History. In ICLR.
[257]
Caleb Ziems, Jane A. Yu, Yi-Chia Wang, Alon Y. Halevy, and Diyi Yang. 2022. The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systems. In ACL.
[258]
Jie Zou, Mohammad Aliannejadi, Evangelos Kanoulas, Maria Soledad Pera, and Yiqun Liu. 2023. Users Meet Clarifying Questions: Toward a Better Understanding of User Interactions for Search Clarification. ACM Trans. Inf. Syst. 41, 1 (2023), 16:1–16:25.
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- Proactive Conversational AI: A Comprehensive Survey of Advancements and Opportunities
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Publication History
Online AM: 24 January 2025
Accepted: 01 January 2025
Revised: 22 November 2024
Received: 28 September 2023
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