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2020 – today
- 2024
[c98]Ahmet Üstün, Viraat Aryabumi, Zheng Xin Yong, Wei-Yin Ko, Daniel D'souza, Gbemileke Onilude, Neel Bhandari, Shivalika Singh, Hui-Lee Ooi, Amr Kayid, Freddie Vargus, Phil Blunsom, Shayne Longpre, Niklas Muennighoff, Marzieh Fadaee, Julia Kreutzer, Sara Hooker:
Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model. ACL (1) 2024: 15894-15939- [c97]Satwik Bhattamishra, Arkil Patel, Phil Blunsom, Varun Kanade:
Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions. ICLR 2024 - [c96]Tom Hosking, Phil Blunsom, Max Bartolo:
Human Feedback is not Gold Standard. ICLR 2024 - [i79]Ahmet Üstün, Viraat Aryabumi, Zheng Xin Yong, Wei-Yin Ko, Daniel D'souza, Gbemileke Onilude, Neel Bhandari, Shivalika Singh, Hui-Lee Ooi, Amr Kayid, Freddie Vargus, Phil Blunsom, Shayne Longpre, Niklas Muennighoff, Marzieh Fadaee, Julia Kreutzer, Sara Hooker:
Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model. CoRR abs/2402.07827 (2024) - [i78]Viraat Aryabumi, John Dang, Dwarak Talupuru, Saurabh Dash, David Cairuz, Hangyu Lin, Bharat Venkitesh, Madeline Smith, Jon Ander Campos, Yi Chern Tan, Kelly Marchisio, Max Bartolo, Sebastian Ruder, Acyr Locatelli, Julia Kreutzer, Nick Frosst, Aidan N. Gomez, Phil Blunsom, Marzieh Fadaee, Ahmet Üstün, Sara Hooker:
Aya 23: Open Weight Releases to Further Multilingual Progress. CoRR abs/2405.15032 (2024) - [i77]Zihuiwen Ye, Fraser Greenlee-Scott, Max Bartolo, Phil Blunsom, Jon Ander Campos, Matthias Gallé:
Improving Reward Models with Synthetic Critiques. CoRR abs/2405.20850 (2024) - [i76]Satwik Bhattamishra, Michael Hahn, Phil Blunsom, Varun Kanade:
Separations in the Representational Capabilities of Transformers and Recurrent Architectures. CoRR abs/2406.09347 (2024) - [i75]Qizhen Zhang, Nikolas Gritsch, Dwaraknath Gnaneshwar, Simon Guo, David Cairuz, Bharat Venkitesh, Jakob N. Foerster, Phil Blunsom, Sebastian Ruder, Ahmet Üstün, Acyr Locatelli:
BAM! Just Like That: Simple and Efficient Parameter Upcycling for Mixture of Experts. CoRR abs/2408.08274 (2024) - 2023
- [c95]Satwik Bhattamishra, Arkil Patel, Varun Kanade, Phil Blunsom:
Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions. ACL (1) 2023: 5767-5791 - [c94]Made Nindyatama Nityasya, Haryo Akbarianto Wibowo, Alham Fikri Aji, Genta Indra Winata, Radityo Eko Prasojo, Phil Blunsom, Adhiguna Kuncoro:
On "Scientific Debt" in NLP: A Case for More Rigour in Language Model Pre-Training Research. ACL (1) 2023: 8554-8572 - [c93]Aishwarya Agrawal, Ivana Kajic, Emanuele Bugliarello, Elnaz Davoodi, Anita Gergely, Phil Blunsom, Aida Nematzadeh:
Reassessing Evaluation Practices in Visual Question Answering: A Case Study on Out-of-Distribution Generalization. EACL (Findings) 2023: 1171-1196 - [c92]Chenghao Xiao, Zihuiwen Ye, G. Thomas Hudson, Zhongtian Sun, Phil Blunsom, Noura Al Moubayed:
Can Text Encoders be Deceived by Length Attack? Tiny Papers @ ICLR 2023 - [c91]Arash Ahmadian, Saurabh Dash, Hongyu Chen, Bharat Venkitesh, Stephen Zhen Gou, Phil Blunsom, Ahmet Üstün, Sara Hooker:
Intriguing Properties of Quantization at Scale. NeurIPS 2023 - [i74]Arash Ahmadian, Saurabh Dash, Hongyu Chen, Bharat Venkitesh, Stephen Gou, Phil Blunsom, Ahmet Üstün, Sara Hooker:
Intriguing Properties of Quantization at Scale. CoRR abs/2305.19268 (2023) - [i73]Made Nindyatama Nityasya, Haryo Akbarianto Wibowo, Alham Fikri Aji, Genta Indra Winata, Radityo Eko Prasojo, Phil Blunsom, Adhiguna Kuncoro:
On "Scientific Debt" in NLP: A Case for More Rigour in Language Model Pre-Training Research. CoRR abs/2306.02870 (2023) - [i72]Kyle Duffy, Satwik Bhattamishra, Phil Blunsom:
Structural Transfer Learning in NL-to-Bash Semantic Parsers. CoRR abs/2307.16795 (2023) - [i71]Tom Hosking, Phil Blunsom, Max Bartolo:
Human Feedback is not Gold Standard. CoRR abs/2309.16349 (2023) - [i70]Satwik Bhattamishra, Arkil Patel, Phil Blunsom, Varun Kanade:
Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions. CoRR abs/2310.03016 (2023) - 2022
- [j17]Gábor Melis, András György, Phil Blunsom:
Mutual Information Constraints for Monte-Carlo Objectives to Prevent Posterior Collapse Especially in Language Modelling. J. Mach. Learn. Res. 23: 75:1-75:36 (2022) - [j16]Qi Liu, Dani Yogatama, Phil Blunsom:
Relational Memory-Augmented Language Models. Trans. Assoc. Comput. Linguistics 10: 555-572 (2022) - [j15]Laurent Sartran, Samuel Barrett, Adhiguna Kuncoro, Milos Stanojevic, Phil Blunsom, Chris Dyer:
Transformer Grammars: Augmenting Transformer Language Models with Syntactic Inductive Biases at Scale. Trans. Assoc. Comput. Linguistics 10: 1423-1439 (2022) - [c90]Arkil Patel, Satwik Bhattamishra, Phil Blunsom, Navin Goyal:
Revisiting the Compositional Generalization Abilities of Neural Sequence Models. ACL (2) 2022: 424-434 - [c89]Qi Liu, Zihuiwen Ye, Tao Yu, Linfeng Song, Phil Blunsom:
Augmenting Multi-Turn Text-to-SQL Datasets with Self-Play. EMNLP (Findings) 2022: 5608-5620 - [c88]Xiang Lorraine Li, Adhiguna Kuncoro, Jordan Hoffmann, Cyprien de Masson d'Autume, Phil Blunsom, Aida Nematzadeh:
A Systematic Investigation of Commonsense Knowledge in Large Language Models. EMNLP 2022: 11838-11855 - [c87]Adam Liska, Tomás Kociský, Elena Gribovskaya, Tayfun Terzi, Eren Sezener, Devang Agrawal, Cyprien de Masson d'Autume, Tim Scholtes, Manzil Zaheer, Susannah Young, Ellen Gilsenan-McMahon, Sophia Austin, Phil Blunsom, Angeliki Lazaridou:
StreamingQA: A Benchmark for Adaptation to New Knowledge over Time in Question Answering Models. ICML 2022: 13604-13622 - [c86]Matthew Morris, Pasquale Minervini, Phil Blunsom:
Learning Proof Path Selection Policies in Neural Theorem Proving. NeSy 2022: 64-87 - [i69]Qi Liu, Dani Yogatama, Phil Blunsom:
Relational Memory Augmented Language Models. CoRR abs/2201.09680 (2022) - [i68]Laurent Sartran, Samuel Barrett, Adhiguna Kuncoro, Milos Stanojevic, Phil Blunsom, Chris Dyer:
Transformer Grammars: Augmenting Transformer Language Models with Syntactic Inductive Biases at Scale. CoRR abs/2203.00633 (2022) - [i67]Arkil Patel, Satwik Bhattamishra, Phil Blunsom, Navin Goyal:
Revisiting the Compositional Generalization Abilities of Neural Sequence Models. CoRR abs/2203.07402 (2022) - [i66]Adam Liska, Tomás Kociský, Elena Gribovskaya, Tayfun Terzi, Eren Sezener, Devang Agrawal, Cyprien de Masson d'Autume, Tim Scholtes, Manzil Zaheer, Susannah Young, Ellen Gilsenan-McMahon, Sophia Austin, Phil Blunsom, Angeliki Lazaridou:
StreamingQA: A Benchmark for Adaptation to New Knowledge over Time in Question Answering Models. CoRR abs/2205.11388 (2022) - [i65]Aishwarya Agrawal, Ivana Kajic, Emanuele Bugliarello, Elnaz Davoodi, Anita Gergely, Phil Blunsom, Aida Nematzadeh:
Rethinking Evaluation Practices in Visual Question Answering: A Case Study on Out-of-Distribution Generalization. CoRR abs/2205.12191 (2022) - [i64]Qi Liu, Zihuiwen Ye, Tao Yu, Phil Blunsom, Linfeng Song:
Augmenting Multi-Turn Text-to-SQL Datasets with Self-Play. CoRR abs/2210.12096 (2022) - [i63]Satwik Bhattamishra, Arkil Patel, Varun Kanade, Phil Blunsom:
Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions. CoRR abs/2211.12316 (2022) - 2021
- [j14]Qi Liu, Lei Yu, Laura Rimell, Phil Blunsom:
Pretraining the Noisy Channel Model for Task-Oriented Dialogue. Trans. Assoc. Comput. Linguistics 9: 657-674 (2021) - [j13]Linhai Xie
, Yishu Miao, Sen Wang, Phil Blunsom, Zhihua Wang, Changhao Chen, Andrew Markham, Niki Trigoni:
Learning With Stochastic Guidance for Robot Navigation. IEEE Trans. Neural Networks Learn. Syst. 32(1): 166-176 (2021) - [c85]Yishu Miao, Phil Blunsom, Lucia Specia:
A Generative Framework for Simultaneous Machine Translation. EMNLP (1) 2021: 6697-6706 - [c84]Qi Liu, Matt J. Kusner, Phil Blunsom:
Counterfactual Data Augmentation for Neural Machine Translation. NAACL-HLT 2021: 187-197 - [c83]Angeliki Lazaridou, Adhiguna Kuncoro, Elena Gribovskaya, Devang Agrawal, Adam Liska, Tayfun Terzi, Mai Gimenez, Cyprien de Masson d'Autume, Tomás Kociský, Sebastian Ruder, Dani Yogatama, Kris Cao, Susannah Young, Phil Blunsom:
Mind the Gap: Assessing Temporal Generalization in Neural Language Models. NeurIPS 2021: 29348-29363 - [i62]Angeliki Lazaridou, Adhiguna Kuncoro, Elena Gribovskaya, Devang Agrawal, Adam Liska, Tayfun Terzi, Mai Gimenez, Cyprien de Masson d'Autume, Sebastian Ruder, Dani Yogatama, Kris Cao, Tomás Kociský, Susannah Young, Phil Blunsom:
Pitfalls of Static Language Modelling. CoRR abs/2102.01951 (2021) - [i61]Qi Liu, Lei Yu, Laura Rimell, Phil Blunsom:
Pretraining the Noisy Channel Model for Task-Oriented Dialogue. CoRR abs/2103.10518 (2021) - [i60]Xiang Lorraine Li, Adhiguna Kuncoro, Cyprien de Masson d'Autume, Phil Blunsom, Aida Nematzadeh:
A Systematic Investigation of Commonsense Understanding in Large Language Models. CoRR abs/2111.00607 (2021) - 2020
- [j12]Lei Yu, Laurent Sartran, Wojciech Stokowiec, Wang Ling, Lingpeng Kong, Phil Blunsom, Chris Dyer:
Better Document-Level Machine Translation with Bayes' Rule. Trans. Assoc. Comput. Linguistics 8: 346-360 (2020) - [j11]Adhiguna Kuncoro, Lingpeng Kong, Daniel Fried, Dani Yogatama, Laura Rimell, Chris Dyer, Phil Blunsom:
Syntactic Structure Distillation Pretraining for Bidirectional Encoders. Trans. Assoc. Comput. Linguistics 8: 776-794 (2020) - [c82]Daniel Fried, Jean-Baptiste Alayrac, Phil Blunsom, Chris Dyer, Stephen Clark, Aida Nematzadeh:
Learning to Segment Actions from Observation and Narration. ACL 2020: 2569-2588 - [c81]Oana-Maria Camburu, Brendan Shillingford, Pasquale Minervini, Thomas Lukasiewicz, Phil Blunsom:
Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations. ACL 2020: 4157-4165 - [c80]Felix Hill, Stephen Clark, Phil Blunsom, Karl Moritz Hermann:
Simulating Early Word Learning in Situated Connectionist Agents. CogSci 2020 - [c79]Gunnar A. Sigurdsson, Jean-Baptiste Alayrac, Aida Nematzadeh, Lucas Smaira, Mateusz Malinowski, João Carreira, Phil Blunsom, Andrew Zisserman:
Visual Grounding in Video for Unsupervised Word Translation. CVPR 2020: 10847-10856 - [c78]Kazuya Kawakami, Luyu Wang, Chris Dyer, Phil Blunsom, Aäron van den Oord:
Learning Robust and Multilingual Speech Representations. EMNLP (Findings) 2020: 1182-1192 - [c77]Gábor Melis, Tomás Kociský, Phil Blunsom:
Mogrifier LSTM. ICLR 2020 - [c76]Lei Yu, Laurent Sartran, Po-Sen Huang, Wojciech Stokowiec, Domenic Donato, Srivatsan Srinivasan, Alek Andreev, Wang Ling, Sona Mokrá, Agustin Dal Lago, Yotam Doron, Susannah Young, Phil Blunsom, Chris Dyer:
The DeepMind Chinese-English Document Translation System at WMT2020. WMT@EMNLP 2020: 326-337 - [i59]Kazuya Kawakami, Luyu Wang, Chris Dyer, Phil Blunsom, Aäron van den Oord:
Learning Robust and Multilingual Speech Representations. CoRR abs/2001.11128 (2020) - [i58]Gunnar A. Sigurdsson, Jean-Baptiste Alayrac, Aida Nematzadeh, Lucas Smaira, Mateusz Malinowski, João Carreira, Phil Blunsom, Andrew Zisserman:
Visual Grounding in Video for Unsupervised Word Translation. CoRR abs/2003.05078 (2020) - [i57]Qi Liu, Matt J. Kusner, Phil Blunsom:
A Survey on Contextual Embeddings. CoRR abs/2003.07278 (2020) - [i56]Daniel Fried, Jean-Baptiste Alayrac, Phil Blunsom, Chris Dyer, Stephen Clark, Aida Nematzadeh:
Learning to Segment Actions from Observation and Narration. CoRR abs/2005.03684 (2020) - [i55]Adhiguna Kuncoro, Lingpeng Kong, Daniel Fried, Dani Yogatama, Laura Rimell, Chris Dyer, Phil Blunsom:
Syntactic Structure Distillation Pretraining For Bidirectional Encoders. CoRR abs/2005.13482 (2020) - [i54]Oana-Maria Camburu, Eleonora Giunchiglia, Jakob N. Foerster, Thomas Lukasiewicz, Phil Blunsom:
The Struggles of Feature-Based Explanations: Shapley Values vs. Minimal Sufficient Subsets. CoRR abs/2009.11023 (2020) - [i53]Gábor Melis, András György, Phil Blunsom:
Mutual Information Constraints for Monte-Carlo Objectives. CoRR abs/2012.00708 (2020)
2010 – 2019
- 2019
- [c75]Changhao Chen, Yishu Miao, Chris Xiaoxuan Lu, Linhai Xie, Phil Blunsom, Andrew Markham, Niki Trigoni:
MotionTransformer: Transferring Neural Inertial Tracking between Domains. AAAI 2019: 8009-8016 - [c74]Adhiguna Kuncoro, Chris Dyer, Laura Rimell, Stephen Clark, Phil Blunsom:
Scalable Syntax-Aware Language Models Using Knowledge Distillation. ACL (1) 2019: 3472-3484 - [c73]Kazuya Kawakami, Chris Dyer, Phil Blunsom:
Learning to Discover, Ground and Use Words with Segmental Neural Language Models. ACL (1) 2019: 6429-6441 - [c72]Vid Kocijan, Oana-Maria Camburu, Ana-Maria Cretu, Yordan Yordanov, Phil Blunsom, Thomas Lukasiewicz:
WikiCREM: A Large Unsupervised Corpus for Coreference Resolution. EMNLP/IJCNLP (1) 2019: 4302-4311 - [i52]Dani Yogatama, Cyprien de Masson d'Autume, Jerome T. Connor, Tomás Kociský, Mike Chrzanowski, Lingpeng Kong, Angeliki Lazaridou, Wang Ling, Lei Yu, Chris Dyer, Phil Blunsom:
Learning and Evaluating General Linguistic Intelligence. CoRR abs/1901.11373 (2019) - [i51]Adhiguna Kuncoro, Chris Dyer, Laura Rimell, Stephen Clark, Phil Blunsom:
Scalable Syntax-Aware Language Models Using Knowledge Distillation. CoRR abs/1906.06438 (2019) - [i50]Vid Kocijan, Oana-Maria Camburu, Ana-Maria Cretu, Yordan Yordanov, Phil Blunsom, Thomas Lukasiewicz:
WikiCREM: A Large Unsupervised Corpus for Coreference Resolution. CoRR abs/1908.08025 (2019) - [i49]Gábor Melis, Tomás Kociský, Phil Blunsom:
Mogrifier LSTM. CoRR abs/1909.01792 (2019) - [i48]Chris Dyer, Gábor Melis, Phil Blunsom:
A Critical Analysis of Biased Parsers in Unsupervised Parsing. CoRR abs/1909.09428 (2019) - [i47]Lei Yu, Laurent Sartran, Wojciech Stokowiec, Wang Ling, Lingpeng Kong, Phil Blunsom, Chris Dyer:
Putting Machine Translation in Context with the Noisy Channel Model. CoRR abs/1910.00553 (2019) - [i46]Oana-Maria Camburu, Eleonora Giunchiglia, Jakob N. Foerster, Thomas Lukasiewicz, Phil Blunsom:
Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods. CoRR abs/1910.02065 (2019) - [i45]Oana-Maria Camburu, Brendan Shillingford, Pasquale Minervini, Thomas Lukasiewicz, Phil Blunsom:
Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations. CoRR abs/1910.03065 (2019) - 2018
- [j10]Tomás Kociský, Jonathan Schwarz, Phil Blunsom, Chris Dyer, Karl Moritz Hermann, Gábor Melis, Edward Grefenstette:
The NarrativeQA Reading Comprehension Challenge. Trans. Assoc. Comput. Linguistics 6: 317-328 (2018) - [c71]Adhiguna Kuncoro, Chris Dyer, John Hale, Dani Yogatama, Stephen Clark, Phil Blunsom:
LSTMs Can Learn Syntax-Sensitive Dependencies Well, But Modeling Structure Makes Them Better. ACL (1) 2018: 1426-1436 - [c70]Gábor Melis, Chris Dyer, Phil Blunsom:
On the State of the Art of Evaluation in Neural Language Models. ICLR (Poster) 2018 - [c69]Dani Yogatama, Yishu Miao, Gábor Melis, Wang Ling, Adhiguna Kuncoro, Chris Dyer, Phil Blunsom:
Memory Architectures in Recurrent Neural Network Language Models. ICLR (Poster) 2018 - [c68]Jan Buys, Phil Blunsom:
Neural Syntactic Generative Models with Exact Marginalization. NAACL-HLT 2018: 942-952 - [c67]Andrew Trask, Felix Hill, Scott E. Reed, Jack W. Rae, Chris Dyer, Phil Blunsom:
Neural Arithmetic Logic Units. NeurIPS 2018: 8046-8055 - [c66]Oana-Maria Camburu, Tim Rocktäschel, Thomas Lukasiewicz, Phil Blunsom:
e-SNLI: Natural Language Inference with Natural Language Explanations. NeurIPS 2018: 9560-9572 - [i44]Gábor Melis, Charles Blundell, Tomás Kociský, Karl Moritz Hermann, Chris Dyer, Phil Blunsom:
Pushing the bounds of dropout. CoRR abs/1805.09208 (2018) - [i43]Tiago Ramalho, Tomás Kociský, Frederic Besse, S. M. Ali Eslami, Gábor Melis, Fabio Viola, Phil Blunsom, Karl Moritz Hermann:
Encoding Spatial Relations from Natural Language. CoRR abs/1807.01670 (2018) - [i42]Andrew Trask, Felix Hill, Scott E. Reed, Jack W. Rae, Chris Dyer, Phil Blunsom:
Neural Arithmetic Logic Units. CoRR abs/1808.00508 (2018) - [i41]Changhao Chen, Yishu Miao, Chris Xiaoxuan Lu, Phil Blunsom, Andrew Markham, Niki Trigoni:
Transferring Physical Motion Between Domains for Neural Inertial Tracking. CoRR abs/1810.02076 (2018) - [i40]Kazuya Kawakami, Chris Dyer, Phil Blunsom:
Unsupervised Word Discovery with Segmental Neural Language Models. CoRR abs/1811.09353 (2018) - [i39]Lei Yu, Cyprien de Masson d'Autume, Chris Dyer, Phil Blunsom, Lingpeng Kong, Wang Ling:
Sentence Encoding with Tree-constrained Relation Networks. CoRR abs/1811.10475 (2018) - [i38]Linhai Xie, Yishu Miao, Sen Wang, Phil Blunsom, Zhihua Wang, Changhao Chen, Andrew Markham, Niki Trigoni:
Learning with Stochastic Guidance for Navigation. CoRR abs/1811.10756 (2018) - [i37]Oana-Maria Camburu, Tim Rocktäschel, Thomas Lukasiewicz, Phil Blunsom:
e-SNLI: Natural Language Inference with Natural Language Explanations. CoRR abs/1812.01193 (2018) - 2017
- [c65]Wang Ling, Dani Yogatama, Chris Dyer, Phil Blunsom:
Program Induction by Rationale Generation: Learning to Solve and Explain Algebraic Word Problems. ACL (1) 2017: 158-167 - [c64]Jan Buys, Phil Blunsom:
Robust Incremental Neural Semantic Graph Parsing. ACL (1) 2017: 1215-1226 - [c63]Kazuya Kawakami, Chris Dyer, Phil Blunsom:
Learning to Create and Reuse Words in Open-Vocabulary Neural Language Modeling. ACL (1) 2017: 1492-1502 - [c62]Zichao Yang, Phil Blunsom, Chris Dyer, Wang Ling:
Reference-Aware Language Models. EMNLP 2017: 1850-1859 - [c61]Dani Yogatama, Phil Blunsom, Chris Dyer, Edward Grefenstette, Wang Ling:
Learning to Compose Words into Sentences with Reinforcement Learning. ICLR (Poster) 2017 - [c60]Lei Yu, Phil Blunsom, Chris Dyer, Edward Grefenstette, Tomás Kociský:
The Neural Noisy Channel. ICLR (Poster) 2017 - [c59]Yishu Miao, Edward Grefenstette, Phil Blunsom:
Discovering Discrete Latent Topics with Neural Variational Inference. ICML 2017: 2410-2419 - [c58]Tsung-Hsien Wen, Yishu Miao, Phil Blunsom, Steve J. Young:
Latent Intention Dialogue Models. ICML 2017: 3732-3741 - [c57]Jan Buys, Phil Blunsom:
Oxford at SemEval-2017 Task 9: Neural AMR Parsing with Pointer-Augmented Attention. SemEval@ACL 2017: 914-919 - [e5]Mirella Lapata, Phil Blunsom, Alexander Koller:
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017, Valencia, Spain, April 3-7, 2017, Volume 1: Long Papers. Association for Computational Linguistics 2017, ISBN 978-1-945626-34-0 [contents] - [e4]Mirella Lapata, Phil Blunsom, Alexander Koller:
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017, Valencia, Spain, April 3-7, 2017, Volume 2: Short Papers. Association for Computational Linguistics 2017, ISBN 978-1-945626-35-7 [contents] - [e3]Phil Blunsom, Antoine Bordes, Kyunghyun Cho, Shay B. Cohen, Chris Dyer, Edward Grefenstette, Karl Moritz Hermann, Laura Rimell, Jason Weston, Scott Yih:
Proceedings of the 2nd Workshop on Representation Learning for NLP, Rep4NLP@ACL 2017, Vancouver, Canada, August 3, 2017. Association for Computational Linguistics 2017, ISBN 978-1-945626-62-3 [contents] - [i36]Dani Yogatama, Chris Dyer, Wang Ling, Phil Blunsom:
Generative and Discriminative Text Classification with Recurrent Neural Networks. CoRR abs/1703.01898 (2017) - [i35]Kazuya Kawakami, Chris Dyer, Phil Blunsom:
Learning to Create and Reuse Words in Open-Vocabulary Neural Language Modeling. CoRR abs/1704.06986 (2017) - [i34]Jan Buys, Phil Blunsom:
Robust Incremental Neural Semantic Graph Parsing. CoRR abs/1704.07092 (2017) - [i33]Wang Ling, Dani Yogatama, Chris Dyer, Phil Blunsom:
Program Induction by Rationale Generation: Learning to Solve and Explain Algebraic Word Problems. CoRR abs/1705.04146 (2017) - [i32]Tsung-Hsien Wen, Yishu Miao, Phil Blunsom, Steve J. Young:
Latent Intention Dialogue Models. CoRR abs/1705.10229 (2017) - [i31]Yishu Miao, Edward Grefenstette, Phil Blunsom:
Discovering Discrete Latent Topics with Neural Variational Inference. CoRR abs/1706.00359 (2017) - [i30]Karl Moritz Hermann, Felix Hill, Simon Green, Fumin Wang, Ryan Faulkner, Hubert Soyer, David Szepesvari, Wojciech Marian Czarnecki, Max Jaderberg, Denis Teplyashin, Marcus Wainwright, Chris Apps, Demis Hassabis, Phil Blunsom:
Grounded Language Learning in a Simulated 3D World. CoRR abs/1706.06551 (2017) - [i29]Gábor Melis, Chris Dyer, Phil Blunsom:
On the State of the Art of Evaluation in Neural Language Models. CoRR abs/1707.05589 (2017) - [i28]Felix Hill, Karl Moritz Hermann, Phil Blunsom, Stephen Clark:
Understanding Grounded Language Learning Agents. CoRR abs/1710.09867 (2017) - [i27]Tomás Kociský, Jonathan Schwarz, Phil Blunsom, Chris Dyer, Karl Moritz Hermann, Gábor Melis, Edward Grefenstette:
The NarrativeQA Reading Comprehension Challenge. CoRR abs/1712.07040 (2017) - [i26]Phil Blunsom, Kyunghyun Cho, Chris Dyer, Hinrich Schütze:
From Characters to Understanding Natural Language (C2NLU): Robust End-to-End Deep Learning for NLP (Dagstuhl Seminar 17042). Dagstuhl Reports 7(1): 129-157 (2017) - 2016
- [j9]Alex Graves, Greg Wayne, Malcolm Reynolds, Tim Harley, Ivo Danihelka, Agnieszka Grabska-Barwinska, Sergio Gomez Colmenarejo, Edward Grefenstette, Tiago Ramalho, John P. Agapiou, Adrià Puigdomènech Badia, Karl Moritz Hermann, Yori Zwols, Georg Ostrovski, Adam Cain, Helen King, Christopher Summerfield, Phil Blunsom, Koray Kavukcuoglu, Demis Hassabis:
Hybrid computing using a neural network with dynamic external memory. Nat. 538(7626): 471-476 (2016) - [c56]Wang Ling, Phil Blunsom, Edward Grefenstette, Karl Moritz Hermann, Tomás Kociský, Fumin Wang, Andrew W. Senior:
Latent Predictor Networks for Code Generation. ACL (1) 2016 - [c55]Yishu Miao, Phil Blunsom:
Language as a Latent Variable: Discrete Generative Models for Sentence Compression. EMNLP 2016: 319-328 - [c54]Tomás Kociský, Gábor Melis, Edward Grefenstette, Chris Dyer, Wang Ling, Phil Blunsom, Karl Moritz Hermann:
Semantic Parsing with Semi-Supervised Sequential Autoencoders. EMNLP 2016: 1078-1087 - [c53]Lei Yu, Jan Buys, Phil Blunsom:
Online Segment to Segment Neural Transduction. EMNLP 2016: 1307-1316 - [c52]Yishu Miao, Lei Yu, Phil Blunsom:
Neural Variational Inference for Text Processing. ICML 2016: 1727-1736 - [c51]Tim Rocktäschel, Edward Grefenstette, Karl Moritz Hermann, Tomás Kociský, Phil Blunsom:
Reasoning about Entailment with Neural Attention. ICLR (Poster) 2016 - [e2]Phil Blunsom, Kyunghyun Cho, Shay B. Cohen, Edward Grefenstette, Karl Moritz Hermann, Laura Rimell, Jason Weston, Scott Wen-tau Yih:
Proceedings of the 1st Workshop on Representation Learning for NLP, Rep4NLP@ACL 2016, Berlin, Germany, August 11, 2016. Association for Computational Linguistics 2016, ISBN 978-1-945626-04-3 [contents] - [i25]Wang Ling, Edward Grefenstette, Karl Moritz Hermann, Tomás Kociský, Andrew W. Senior, Fumin Wang, Phil Blunsom:
Latent Predictor Networks for Code Generation. CoRR abs/1603.06744 (2016) - [i24]Jeremy Appleyard, Tomás Kociský, Phil Blunsom:
Optimizing Performance of Recurrent Neural Networks on GPUs. CoRR abs/1604.01946 (2016) - [i23]Yishu Miao, Phil Blunsom:
Language as a Latent Variable: Discrete Generative Models for Sentence Compression. CoRR abs/1609.07317 (2016) - [i22]Lei Yu, Jan Buys, Phil Blunsom:
Online Segment to Segment Neural Transduction. CoRR abs/1609.08194 (2016) - [i21]Tomás Kociský, Gábor Melis, Edward Grefenstette, Chris Dyer, Wang Ling, Phil Blunsom, Karl Moritz Hermann:
Semantic Parsing with Semi-Supervised Sequential Autoencoders. CoRR abs/1609.09315 (2016) - [i20]Zichao Yang, Phil Blunsom, Chris Dyer, Wang Ling:
Reference-Aware Language Models. CoRR abs/1611.01628 (2016) - [i19]Lei Yu, Phil Blunsom, Chris Dyer, Edward Grefenstette, Tomás Kociský:
The Neural Noisy Channel. CoRR abs/1611.02554 (2016) - [i18]Dani Yogatama, Phil Blunsom, Chris Dyer, Edward Grefenstette, Wang Ling:
Learning to Compose Words into Sentences with Reinforcement Learning. CoRR abs/1611.09100 (2016) - 2015
- [j8]Zhuoling Xiao, Hongkai Wen, Andrew Markham, Niki Trigoni, Phil Blunsom, Jeff Frolik:
Non-Line-of-Sight Identification and Mitigation Using Received Signal Strength. IEEE Trans. Wirel. Commun. 14(3): 1689-1702 (2015) - [c50]Jan Buys, Phil Blunsom:
Generative Incremental Dependency Parsing with Neural Networks. ACL (2) 2015: 863-869 - [c49]Jan Buys, Phil Blunsom:
A Bayesian Model for Generative Transition-based Dependency Parsing. DepLing 2015: 58-67 - [c48]Alex Wilson, Phil Blunsom, Andrew D. Ker:
Detection of Steganographic Techniques on Twitter. EMNLP 2015: 2564-2569 - [c47]Paul Baltescu, Phil Blunsom:
Pragmatic Neural Language Modelling in Machine Translation. HLT-NAACL 2015: 820-829 - [c46]Karl Moritz Hermann, Tomás Kociský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, Phil Blunsom:
Teaching Machines to Read and Comprehend. NIPS 2015: 1693-1701 - [c45]Edward Grefenstette, Karl Moritz Hermann, Mustafa Suleyman, Phil Blunsom:
Learning to Transduce with Unbounded Memory. NIPS 2015: 1828-1836 - [e1]Phil Blunsom, Shay B. Cohen, Paramveer S. Dhillon, Percy Liang:
Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing, VS@NAACL-HLT 2015, June 5, 2015, Denver, Colorado, USA. The Association for Computational Linguistics 2015, ISBN 978-1-941643-46-4 [contents] - [i17]Edward Grefenstette, Karl Moritz Hermann, Mustafa Suleyman, Phil Blunsom:
Learning to Transduce with Unbounded Memory. CoRR abs/1506.02516 (2015) - [i16]Karl Moritz Hermann, Tomás Kociský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, Phil Blunsom:
Teaching Machines to Read and Comprehend. CoRR abs/1506.03340 (2015) - [i15]Jan Buys, Phil Blunsom:
A Bayesian Model for Generative Transition-based Dependency Parsing. CoRR abs/1506.04334 (2015) - [i14]Yishu Miao, Lei Yu, Phil Blunsom:
Neural Variational Inference for Text Processing. CoRR abs/1511.06038 (2015) - 2014
- [j7]Paul Baltescu, Phil Blunsom:
A Fast and Simple Online Synchronous Context Free Grammar Extractor. Prague Bull. Math. Linguistics 102: 17-26 (2014) - [j6]Austin Matthews, Paul Baltescu, Phil Blunsom, Alon Lavie, Chris Dyer:
Tree Transduction Tools for cdec. Prague Bull. Math. Linguistics 102: 27-36 (2014) - [j5]Paul Baltescu, Phil Blunsom, Hieu Hoang:
OxLM: A Neural Language Modelling Framework for Machine Translation. Prague Bull. Math. Linguistics 102: 81-92 (2014) - [c44]Edward Grefenstette, Karl Moritz Hermann, Georgiana Dinu, Phil Blunsom:
New Directions in Vector Space Models of Meaning. ACL (Tutorial Abstracts) 2014: 8 - [c43]Karl Moritz Hermann, Phil Blunsom:
Multilingual Models for Compositional Distributed Semantics. ACL (1) 2014: 58-68 - [c42]Tomás Kociský, Karl Moritz Hermann, Phil Blunsom:
Learning Bilingual Word Representations by Marginalizing Alignments. ACL (2) 2014: 224-229 - [c41]Nal Kalchbrenner, Edward Grefenstette, Phil Blunsom:
A Convolutional Neural Network for Modelling Sentences. ACL (1) 2014: 655-665 - [c40]Gregory Dubbin, Phil Blunsom:
Modelling the Lexicon in Unsupervised Part of Speech Induction. EACL 2014: 116-125 - [c39]Eva Hasler, Phil Blunsom, Philipp Koehn, Barry Haddow:
Dynamic Topic Adaptation for Phrase-based MT. EACL 2014: 328-337 - [c38]Jan A. Botha, Phil Blunsom:
Compositional Morphology for Word Representations and Language Modelling. ICML 2014: 1899-1907 - [c37]Alex Wilson, Phil Blunsom, Andrew D. Ker:
Linguistic steganography on Twitter: hierarchical language modeling with manual interaction. Media Watermarking, Security, and Forensics 2014: 902803 - [c36]Karl Moritz Hermann, Phil Blunsom:
A Simple Model for Learning Multilingual Compositional Semantics. ICLR 2014 - [i13]Gregory Dubbin, Phil Blunsom:
Modelling the Lexicon in Unsupervised Part of Speech Induction. CoRR abs/1402.6516 (2014) - [i12]Nal Kalchbrenner, Edward Grefenstette, Phil Blunsom:
A Convolutional Neural Network for Modelling Sentences. CoRR abs/1404.2188 (2014) - [i11]Karl Moritz Hermann, Phil Blunsom:
Multilingual Models for Compositional Distributed Semantics. CoRR abs/1404.4641 (2014) - [i10]Edward Grefenstette, Phil Blunsom, Nando de Freitas, Karl Moritz Hermann:
A Deep Architecture for Semantic Parsing. CoRR abs/1404.7296 (2014) - [i9]Tomás Kociský, Karl Moritz Hermann, Phil Blunsom:
Learning Bilingual Word Representations by Marginalizing Alignments. CoRR abs/1405.0947 (2014) - [i8]Jan A. Botha, Phil Blunsom:
Compositional Morphology for Word Representations and Language Modelling. CoRR abs/1405.4273 (2014) - [i7]Misha Denil, Alban Demiraj, Nal Kalchbrenner, Phil Blunsom, Nando de Freitas:
Modelling, Visualising and Summarising Documents with a Single Convolutional Neural Network. CoRR abs/1406.3830 (2014) - [i6]Dimitrios Kotzias, Misha Denil, Phil Blunsom, Nando de Freitas:
Deep Multi-Instance Transfer Learning. CoRR abs/1411.3128 (2014) - [i5]Lei Yu, Karl Moritz Hermann, Phil Blunsom, Stephen Pulman:
Deep Learning for Answer Sentence Selection. CoRR abs/1412.1632 (2014) - [i4]Paul Baltescu, Phil Blunsom:
Pragmatic Neural Language Modelling in Machine Translation. CoRR abs/1412.7119 (2014) - [i3]Yishu Miao, Ziyu Wang, Phil Blunsom:
Bayesian Optimisation for Machine Translation. CoRR abs/1412.7180 (2014) - 2013
- [c35]Karl Moritz Hermann, Edward Grefenstette, Phil Blunsom:
"Not not bad" is not "bad": A distributional account of negation. CVSM@ACL 2013: 74-82 - [c34]Nal Kalchbrenner, Phil Blunsom:
Recurrent Convolutional Neural Networks for Discourse Compositionality. CVSM@ACL 2013: 119-126 - [c33]Karl Moritz Hermann, Phil Blunsom:
The Role of Syntax in Vector Space Models of Compositional Semantics. ACL (1) 2013: 894-904 - [c32]Pengyu Wang, Phil Blunsom:
Collapsed Variational Bayesian Inference for Hidden Markov Models. AISTATS 2013: 599-607 - [c31]Pengyu Wang, Phil Blunsom:
Collapsed Variational Bayesian Inference for PCFGs. CoNLL 2013: 173-182 - [c30]Jan A. Botha, Phil Blunsom:
Adaptor Grammars for Learning Non-Concatenative Morphology. EMNLP 2013: 345-356 - [c29]Nal Kalchbrenner, Phil Blunsom:
Recurrent Continuous Translation Models. EMNLP 2013: 1700-1709 - [c28]Hongkai Wen, Zhuoling Xiao, Niki Trigoni, Phil Blunsom:
On Assessing the Accuracy of Positioning Systems in Indoor Environments. EWSN 2013: 1-17 - [c27]Yarin Gal, Phil Blunsom:
A Systematic Bayesian Treatment of the IBM Alignment Models. HLT-NAACL 2013: 969-977 - [c26]Zhuoling Xiao, Hongkai Wen, Andrew Markham, Niki Trigoni, Phil Blunsom, Jeff Frolik:
Identification and mitigation of non-line-of-sight conditions using received signal strength. WiMob 2013: 667-674 - [i2]Karl Moritz Hermann, Edward Grefenstette, Phil Blunsom:
"Not not bad" is not "bad": A distributional account of negation. CoRR abs/1306.2158 (2013) - [i1]Nal Kalchbrenner, Phil Blunsom:
Recurrent Convolutional Neural Networks for Discourse Compositionality. CoRR abs/1306.3584 (2013) - 2012
- [c25]Jan A. Botha, Chris Dyer, Phil Blunsom:
Bayesian Language Modelling of German Compounds. COLING 2012: 341-356 - [c24]Abby D. Levenberg, Chris Dyer, Phil Blunsom:
A Bayesian Model for Learning SCFGs with Discontiguous Rules. EMNLP-CoNLL 2012: 223-232 - [c23]Gregory Dubbin, Phil Blunsom:
Unsupervised Bayesian Part of Speech Inference with Particle Gibbs. ECML/PKDD (1) 2012: 760-773 - [c22]Karl Moritz Hermann, Chris Dyer, Phil Blunsom, Stephen Pulman:
Learning Semantics and Selectional Preference of Adjective-Noun Pairs. *SEM@NAACL-HLT 2012: 70-74 - [c21]Karl Moritz Hermann, Phil Blunsom, Stephen Pulman:
An Unsupervised Ranking Model for Noun-Noun Compositionality. *SEM@NAACL-HLT 2012: 132-141 - 2011
- [c20]Phil Blunsom, Trevor Cohn:
A Hierarchical Pitman-Yor Process HMM for Unsupervised Part of Speech Induction. ACL 2011: 865-874 - 2010
- [j4]Trevor Cohn, Phil Blunsom, Sharon Goldwater:
Inducing Tree-Substitution Grammars. J. Mach. Learn. Res. 11: 3053-3096 (2010) - [j3]Alexandra Birch, Miles Osborne, Phil Blunsom:
Metrics for MT evaluation: evaluating reordering. Mach. Transl. 24(1): 15-26 (2010) - [j2]Abhishek Arun, Barry Haddow, Philipp Koehn, Adam Lopez, Chris Dyer, Phil Blunsom:
Monte Carlo techniques for phrase-based translation. Mach. Transl. 24(2): 103-121 (2010) - [c19]Chris Dyer, Adam Lopez, Juri Ganitkevitch, Jonathan Weese, Ferhan Türe, Phil Blunsom, Hendra Setiawan, Vladimir Eidelman, Philip Resnik:
cdec: A Decoder, Alignment, and Learning Framework for Finite-State and Context-Free Translation Models. ACL (System Demonstrations) 2010: 7-12 - [c18]Trevor Cohn, Phil Blunsom:
Blocked Inference in Bayesian Tree Substitution Grammars. ACL (2) 2010: 225-230 - [c17]Phil Blunsom, Trevor Cohn:
Unsupervised Induction of Tree Substitution Grammars for Dependency Parsing. EMNLP 2010: 1204-1213 - [c16]Phil Blunsom, Trevor Cohn:
Inducing Synchronous Grammars with Slice Sampling. HLT-NAACL 2010: 238-241
2000 – 2009
- 2009
- [j1]Phil Blunsom:
Learning Machine Translation - Cyril Goutte, Nicola Cancedda, Marc Dymetman, and George Foster (editors) The MIT Press, 2009, xii+316 pp; ISBN 978-0-262-07297-7. Comput. Linguistics 35(4): 637-640 (2009) - [c15]Phil Blunsom, Trevor Cohn, Sharon Goldwater, Mark Johnson:
A Note on the Implementation of Hierarchical Dirichlet Processes. ACL/IJCNLP (2) 2009: 337-340 - [c14]Phil Blunsom, Trevor Cohn, Chris Dyer, Miles Osborne:
A Gibbs Sampler for Phrasal Synchronous Grammar Induction. ACL/IJCNLP 2009: 782-790 - [c13]Abhishek Arun, Chris Dyer, Barry Haddow, Phil Blunsom, Adam Lopez, Philipp Koehn:
Monte Carlo inference and maximization for phrase-based translation. CoNLL 2009: 102-110 - [c12]Trevor Cohn, Phil Blunsom:
A Bayesian Model of Syntax-Directed Tree to String Grammar Induction. EMNLP 2009: 352-361 - [c11]Trevor Cohn, Sharon Goldwater, Phil Blunsom:
Inducing Compact but Accurate Tree-Substitution Grammars. HLT-NAACL 2009: 548-556 - [c10]Alexandra Birch, Phil Blunsom, Miles Osborne:
A Quantitative Analysis of Reordering Phenomena. WMT@EACL 2009: 197-205 - 2008
- [c9]Phil Blunsom, Trevor Cohn, Miles Osborne:
A Discriminative Latent Variable Model for Statistical Machine Translation. ACL 2008: 200-208 - [c8]Phil Blunsom, Miles Osborne:
Probabilistic Inference for Machine Translation. EMNLP 2008: 215-223 - [c7]Phil Blunsom, Trevor Cohn, Miles Osborne:
Bayesian Synchronous Grammar Induction. NIPS 2008: 161-168 - 2007
- [b1]Phil Blunsom:
Structured classification for multilingual natural language processing. University of Melbourne, Australia, 2007 - 2006
- [c6]Phil Blunsom, Trevor Cohn:
Discriminative Word Alignment with Conditional Random Fields. ACL 2006 - [c5]Jeremy Nicholson, Timothy Baldwin, Phil Blunsom:
Die Morphologie (f): Targeted Lexical Acquisition for Languages other than English. ALTA 2006: 67-74 - [c4]Phil Blunsom, Timothy Baldwin:
Multilingual Deep Lexical Acquisition for HPSGs via Supertagging. EMNLP 2006: 164-171 - [c3]Phil Blunsom, Krystle Kocik, James R. Curran:
Question classification with log-linear models. SIGIR 2006: 615-616 - 2005
- [c2]Trevor Cohn, Phil Blunsom:
Semantic Role Labelling with Tree Conditional Random Fields. CoNLL 2005: 169-172 - 2004
- [c1]Phil Blunsom:
Maximum Entropy Markov Models for Semantic Role Labelling. ALTA 2004: 109-116
Coauthor Index
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