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ORCID16th INLG 2023: Prague, Czechia - Generation Challenges
- Simon Mille:
Proceedings of the 16th International Natural Language Generation Conference, INLG 2023 - Generation Challenges, Prague, Czechia, September 11 - 15, 2023. Association for Computational Linguistics 2023, ISBN 979-8-89176-003-5 - Khyathi Raghavi Chandu, David M. Howcroft, Dimitra Gkatzia, Yi-Ling Chung, Yufang Hou, Chris Chinenye Emezue, Pawan Rajpoot, Tosin P. Adewumi:
LOWRECORP: the Low-Resource NLG Corpus Building Challenge. 1-9 - Nikolay Mikhaylovskiy:
Long Story Generation Challenge. 10-16 - Xudong Hong, Khushboo Mehra, Asad B. Sayeed, Vera Demberg:
Visually Grounded Story Generation Challenge. 17-22 - Nikolai Ilinykh, Simon Dobnik:
The VDG Challenge: Response Generation and Evaluation in Collaborative Visual Dialogue. 23-30 - Maja Stahl
, Henning Wachsmuth:
Identifying Feedback Types to Augment Feedback Comment Generation. 31-36 - Nikolay Babakov, Maria Lysyuk, Alexander Shvets, Lilya Kazakova, Alexander Panchenko:
Error syntax aware augmentation of feedback comment generation dataset. 37-44 - Ryo Nagata, Masato Hagiwara, Kazuaki Hanawa, Masato Mita:
A Report on FCG GenChal 2022: Shared Task on Feedback Comment Generation for Language Learners. 45-52 - Shabnam Behzad, Amir Zeldes, Nathan Schneider:
Sentence-level Feedback Generation for English Language Learners: Does Data Augmentation Help? 53-59 - Mana Ihori, Hiroshi Sato, Tomohiro Tanaka, Ryo Masumura:
Retrieval, Masking, and Generation: Feedback Comment Generation using Masked Comment Examples. 60-67 - Naoya Ueda, Mamoru Komachi:
TMU Feedback Comment Generation System Using Pretrained Sequence-to-Sequence Language Models. 68-73 - Shota Koyama, Hiroya Takamura, Naoaki Okazaki:
The Tokyo Tech and AIST System at the GenChal 2022 Shared Task on Feedback Comment Generation. 74-78 - Kunitaka Jimichi, Kotaro Funakoshi, Manabu Okumura:
Feedback comment generation using predicted grammatical terms. 79-83 - Yoshinobu Kano, Neo Watanabe, Kaito Kagaminuma, Claus Aranha, Jaewon Lee, Benedek Hauer, Hisaichi Shibata, Soichiro Miki, Yuta Nakamura, Takuya Okubo, Soga Shigemura, Rei Ito, Kazuki Takashima, Tomoki Fukuda, Masahiro Wakutani, Tomoya Hatanaka, Mami Uchida, Mikio Abe, Akihiro Mikami, Takashi Otsuki, Zhiyang Qi, Kei Harada, Michimasa Inaba, Daisuke Katagami, Hirotaka Osawa, Fujio Toriumi:
AIWolfDial 2023: Summary of Natural Language Division of 5th International AIWolf Contest. 84-100 - Felix Schneider, Marco Turchi:
Team Zoom @ AutoMin 2023: Utilizing Topic Segmentation And LLM Data Augmentation For Long-Form Meeting Summarization. 101-107 - Kristýna Klesnilová, Michelle Elizabeth:
Team Synapse @ AutoMin 2023: Leveraging BART-Based Models for Automatic Meeting Minuting. 108-113 - Frantisek Kmjec, Ondrej Bojar:
Team Iterate @ AutoMin 2023 - Experiments with Iterative Minuting. 114-120 - Ismaël Rousseau, Loïc Fosse, Youness Dkhissi, Géraldine Damnati, Gwénolé Lecorvé:
Darbarer @ AutoMin2023: Transcription simplification for concise minute generation from multi-party conversations. 121-131 - Eugene Borisov, Nikolay Mikhaylovskiy:
Team NTR @ AutoMin 2023: Dolly LLM Improves Minuting Performance, Semantic Segmentation Doesn't. 132-137 - Tirthankar Ghosal, Ondrej Bojar, Marie Hledíková, Tom Kocmi, Anna Nedoluzhko:
Overview of the Second Shared Task on Automatic Minuting (AutoMin) at INLG 2023. 138-167
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