| 2025 | NAACL | Improving Reward Models with Synthetic Critiques. | Zihuiwen Ye, Fraser Greenlee-Scott, Max Bartolo, Phil Blunsom, Jon Ander Campos, Matthias Gall |
| 2024 | ACL | Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model. | Ahmet stn, 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 |
| 2024 | ICLR | Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions. | Satwik Bhattamishra, Arkil Patel, Phil Blunsom, Varun Kanade |
| 2024 | ICLR | Human Feedback is not Gold Standard. | Tom Hosking, Phil Blunsom, Max Bartolo |
| 2023 | ACL | Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions. | Satwik Bhattamishra, Arkil Patel, Varun Kanade, Phil Blunsom |
| 2023 | ACL | On "Scientific Debt" in NLP: A Case for More Rigour in Language Model Pre-Training Research. | Made Nindyatama Nityasya, Haryo Akbarianto Wibowo, Alham Fikri Aji, Genta Indra Winata, Radityo Eko Prasojo, Phil Blunsom, Adhiguna Kuncoro |
| 2023 | EACL | Reassessing Evaluation Practices in Visual Question Answering: A Case Study on Out-of-Distribution Generalization. | Aishwarya Agrawal, Ivana Kajic, Emanuele Bugliarello, Elnaz Davoodi, Anita Gergely, Phil Blunsom, Aida Nematzadeh |
| 2023 | ICLR | Can Text Encoders be Deceived by Length Attack? | Chenghao Xiao, Zihuiwen Ye, G. Thomas Hudson, Zhongtian Sun, Phil Blunsom, Noura Al Moubayed |
| 2022 | ACL | Revisiting the Compositional Generalization Abilities of Neural Sequence Models. | Arkil Patel, Satwik Bhattamishra, Phil Blunsom, Navin Goyal |
| 2022 | EMNLP | A Systematic Investigation of Commonsense Knowledge in Large Language Models. | Xiang Lorraine Li, Adhiguna Kuncoro, Jordan Hoffmann, Cyprien de Masson d'Autume, Phil Blunsom, Aida Nematzadeh |
| 2022 | EMNLP | Augmenting Multi-Turn Text-to-SQL Datasets with Self-Play. | Qi Liu, Zihuiwen Ye, Tao Yu, Linfeng Song, Phil Blunsom |
| 2022 | ICML | StreamingQA: A Benchmark for Adaptation to New Knowledge over Time in Question Answering Models. | Adam Liska, Toms Kocisk, 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 |
| 2022 | NeSy | Learning Proof Path Selection Policies in Neural Theorem Proving. | Matthew Morris, Pasquale Minervini, Phil Blunsom |
| 2021 | EMNLP | A Generative Framework for Simultaneous Machine Translation. | Yishu Miao, Phil Blunsom, Lucia Specia |
| 2021 | NAACL | Counterfactual Data Augmentation for Neural Machine Translation. | Qi Liu, Matt J. Kusner, Phil Blunsom |
| 2020 | ACL | Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations. | Oana-Maria Camburu, Brendan Shillingford, Pasquale Minervini, Thomas Lukasiewicz, Phil Blunsom |
| 2020 | ACL | Learning to Segment Actions from Observation and Narration. | Daniel Fried, Jean-Baptiste Alayrac, Phil Blunsom, Chris Dyer, Stephen Clark, Aida Nematzadeh |
| 2020 | CogSci | Simulating Early Word Learning in Situated Connectionist Agents. | Felix Hill, Stephen Clark, Phil Blunsom, Karl Moritz Hermann |
| 2020 | CVPR | Visual Grounding in Video for Unsupervised Word Translation. | Gunnar A. Sigurdsson, Jean-Baptiste Alayrac, Aida Nematzadeh, Lucas Smaira, Mateusz Malinowski, Joo Carreira, Phil Blunsom, Andrew Zisserman |
| 2020 | EMNLP | Learning Robust and Multilingual Speech Representations. | Kazuya Kawakami, Luyu Wang, Chris Dyer, Phil Blunsom, Aron van den Oord |
| 2020 | ICLR | Mogrifier LSTM. | Gbor Melis, Toms Kocisk, Phil Blunsom |
| 2019 | AAAI | MotionTransformer: Transferring Neural Inertial Tracking between Domains. | Changhao Chen, Yishu Miao, Chris Xiaoxuan Lu, Linhai Xie, Phil Blunsom, Andrew Markham, Niki Trigoni |
| 2019 | ACL | Learning to Discover, Ground and Use Words with Segmental Neural Language Models. | Kazuya Kawakami, Chris Dyer, Phil Blunsom |
| 2019 | ACL | Scalable Syntax-Aware Language Models Using Knowledge Distillation. | Adhiguna Kuncoro, Chris Dyer, Laura Rimell, Stephen Clark, Phil Blunsom |
| 2019 | EMNLP | WikiCREM: A Large Unsupervised Corpus for Coreference Resolution. | Vid Kocijan, Oana-Maria Camburu, Ana-Maria Cretu, Yordan Yordanov, Phil Blunsom, Thomas Lukasiewicz |
| 2018 | ACL | LSTMs Can Learn Syntax-Sensitive Dependencies Well, But Modeling Structure Makes Them Better. | Adhiguna Kuncoro, Chris Dyer, John Hale, Dani Yogatama, Stephen Clark, Phil Blunsom |
| 2018 | ICLR | On the State of the Art of Evaluation in Neural Language Models. | Gbor Melis, Chris Dyer, Phil Blunsom |
| 2018 | ICLR | Memory Architectures in Recurrent Neural Network Language Models. | Dani Yogatama, Yishu Miao, Gbor Melis, Wang Ling, Adhiguna Kuncoro, Chris Dyer, Phil Blunsom |
| 2018 | NAACL | Neural Syntactic Generative Models with Exact Marginalization. | Jan Buys, Phil Blunsom |
| 2017 | ACL | Robust Incremental Neural Semantic Graph Parsing. | Jan Buys, Phil Blunsom |
| 2017 | ACL | Learning to Create and Reuse Words in Open-Vocabulary Neural Language Modeling. | Kazuya Kawakami, Chris Dyer, Phil Blunsom |
| 2017 | ACL | Program Induction by Rationale Generation: Learning to Solve and Explain Algebraic Word Problems. | Wang Ling, Dani Yogatama, Chris Dyer, Phil Blunsom |
| 2017 | EMNLP | Reference-Aware Language Models. | Zichao Yang, Phil Blunsom, Chris Dyer, Wang Ling |
| 2017 | ICLR | Learning to Compose Words into Sentences with Reinforcement Learning. | Dani Yogatama, Phil Blunsom, Chris Dyer, Edward Grefenstette, Wang Ling |
| 2017 | ICLR | The Neural Noisy Channel. | Lei Yu, Phil Blunsom, Chris Dyer, Edward Grefenstette, Toms Kocisk |
| 2017 | ICML | Discovering Discrete Latent Topics with Neural Variational Inference. | Yishu Miao, Edward Grefenstette, Phil Blunsom |
| 2017 | ICML | Latent Intention Dialogue Models. | Tsung-Hsien Wen, Yishu Miao, Phil Blunsom, Steve J. Young |
| 2016 | ACL | Latent Predictor Networks for Code Generation. | Wang Ling, Phil Blunsom, Edward Grefenstette, Karl Moritz Hermann, Toms Kocisk, Fumin Wang, Andrew W. Senior |
| 2016 | EMNLP | Semantic Parsing with Semi-Supervised Sequential Autoencoders. | Toms Kocisk, Gbor Melis, Edward Grefenstette, Chris Dyer, Wang Ling, Phil Blunsom, Karl Moritz Hermann |
| 2016 | EMNLP | Language as a Latent Variable: Discrete Generative Models for Sentence Compression. | Yishu Miao, Phil Blunsom |
| 2016 | EMNLP | Online Segment to Segment Neural Transduction. | Lei Yu, Jan Buys, Phil Blunsom |
| 2016 | ICML | Neural Variational Inference for Text Processing. | Yishu Miao, Lei Yu, Phil Blunsom |
| 2015 | ACL | Generative Incremental Dependency Parsing with Neural Networks. | Jan Buys, Phil Blunsom |
| 2015 | EMNLP | Detection of Steganographic Techniques on Twitter. | Alex Wilson, Phil Blunsom, Andrew D. Ker |
| 2015 | NAACL | Pragmatic Neural Language Modelling in Machine Translation. | Paul Baltescu, Phil Blunsom |
| 2014 | ACL | New Directions in Vector Space Models of Meaning. | Edward Grefenstette, Karl Moritz Hermann, Georgiana Dinu, Phil Blunsom |
| 2014 | ACL | Multilingual Models for Compositional Distributed Semantics. | Karl Moritz Hermann, Phil Blunsom |
| 2014 | ACL | A Convolutional Neural Network for Modelling Sentences. | Nal Kalchbrenner, Edward Grefenstette, Phil Blunsom |
| 2014 | ACL | Learning Bilingual Word Representations by Marginalizing Alignments. | Toms Kocisk, Karl Moritz Hermann, Phil Blunsom |
| 2014 | EACL | Modelling the Lexicon in Unsupervised Part of Speech Induction. | Gregory Dubbin, Phil Blunsom |
| 2014 | EACL | Dynamic Topic Adaptation for Phrase-based MT. | Eva Hasler, Phil Blunsom, Philipp Koehn, Barry Haddow |
| 2014 | ICML | Compositional Morphology for Word Representations and Language Modelling. | Jan A. Botha, Phil Blunsom |
| 2013 | ACL | The Role of Syntax in Vector Space Models of Compositional Semantics. | Karl Moritz Hermann, Phil Blunsom |
| 2013 | ACL | "Not not bad" is not "bad": A distributional account of negation. | Karl Moritz Hermann, Edward Grefenstette, Phil Blunsom |
| 2013 | ACL | Recurrent Convolutional Neural Networks for Discourse Compositionality. | Nal Kalchbrenner, Phil Blunsom |
| 2013 | AISTATS | Collapsed Variational Bayesian Inference for Hidden Markov Models. | Pengyu Wang, Phil Blunsom |
| 2013 | CoNLL | Collapsed Variational Bayesian Inference for PCFGs. | Pengyu Wang, Phil Blunsom |
| 2013 | EMNLP | Adaptor Grammars for Learning Non-Concatenative Morphology. | Jan A. Botha, Phil Blunsom |
| 2013 | EMNLP | Recurrent Continuous Translation Models. | Nal Kalchbrenner, Phil Blunsom |
| 2013 | EWSN | On Assessing the Accuracy of Positioning Systems in Indoor Environments. | Hongkai Wen, Zhuoling Xiao, Niki Trigoni, Phil Blunsom |
| 2013 | NAACL | A Systematic Bayesian Treatment of the IBM Alignment Models. | Yarin Gal, Phil Blunsom |
| 2013 | WiMob | Identification and mitigation of non-line-of-sight conditions using received signal strength. | Zhuoling Xiao, Hongkai Wen, Andrew Markham, Niki Trigoni, Phil Blunsom, Jeff Frolik |
| 2012 | COLING | Bayesian Language Modelling of German Compounds. | Jan A. Botha, Chris Dyer, Phil Blunsom |
| 2012 | EMNLP | A Bayesian Model for Learning SCFGs with Discontiguous Rules. | Abby D. Levenberg, Chris Dyer, Phil Blunsom |
| 2011 | ACL | A Hierarchical Pitman-Yor Process HMM for Unsupervised Part of Speech Induction. | Phil Blunsom, Trevor Cohn |
| 2010 | ACL | Blocked Inference in Bayesian Tree Substitution Grammars. | Trevor Cohn, Phil Blunsom |
| 2010 | ACL | cdec: A Decoder, Alignment, and Learning Framework for Finite-State and Context-Free Translation Models. | Chris Dyer, Adam Lopez, Juri Ganitkevitch, Jonathan Weese, Ferhan Tre, Phil Blunsom, Hendra Setiawan, Vladimir Eidelman, Philip Resnik |
| 2010 | EMNLP | Unsupervised Induction of Tree Substitution Grammars for Dependency Parsing. | Phil Blunsom, Trevor Cohn |
| 2010 | NAACL | Inducing Synchronous Grammars with Slice Sampling. | Phil Blunsom, Trevor Cohn |
| 2009 | ACL | A Gibbs Sampler for Phrasal Synchronous Grammar Induction. | Phil Blunsom, Trevor Cohn, Chris Dyer, Miles Osborne |
| 2009 | ACL | A Note on the Implementation of Hierarchical Dirichlet Processes. | Phil Blunsom, Trevor Cohn, Sharon Goldwater, Mark Johnson |
| 2009 | CoNLL | Monte Carlo inference and maximization for phrase-based translation. | Abhishek Arun, Chris Dyer, Barry Haddow, Phil Blunsom, Adam Lopez, Philipp Koehn |
| 2009 | EMNLP | A Bayesian Model of Syntax-Directed Tree to String Grammar Induction. | Trevor Cohn, Phil Blunsom |
| 2009 | NAACL | Inducing Compact but Accurate Tree-Substitution Grammars. | Trevor Cohn, Sharon Goldwater, Phil Blunsom |
| 2008 | ACL | A Discriminative Latent Variable Model for Statistical Machine Translation. | Phil Blunsom, Trevor Cohn, Miles Osborne |
| 2008 | EMNLP | Probabilistic Inference for Machine Translation. | Phil Blunsom, Miles Osborne |
| 2006 | ACL | Discriminative Word Alignment with Conditional Random Fields. | Phil Blunsom, Trevor Cohn |
| 2006 | EMNLP | Multilingual Deep Lexical Acquisition for HPSGs via Supertagging. | Phil Blunsom, Timothy Baldwin |
| 2006 | SIGIR | Question classification with log-linear models. | Phil Blunsom, Krystle Kocik, James R. Curran |
| 2005 | CoNLL | Semantic Role Labelling with Tree Conditional Random Fields. | Trevor Cohn, Phil Blunsom |