Maximum Entropy Markov Models for Semantic Role Labelling. - Phil Blunsom (ALTA, 2004)

Semantic Role Labelling with Tree Conditional Random Fields. - Trevor Cohn; Phil Blunsom (CoNLL, 2005)

Die Morphologie (f): Targeted Lexical Acquisition for Languages other than English. - Jeremy Nicholson; Timothy Baldwin; Phil Blunsom (ALTA, 2006)

Discriminative Word Alignment with Conditional Random Fields. - Phil Blunsom; Trevor Cohn (ACL, 2006)

Multilingual Deep Lexical Acquisition for HPSGs via Supertagging. - Phil Blunsom; Timothy Baldwin (EMNLP, 2006)

Question classification with log-linear models. - Phil Blunsom; Krystle Kocik; James R. Curran (SIGIR, 2006)

Structured classification for multilingual natural language processing. - Phil Blunsom (2007)

A Discriminative Latent Variable Model for Statistical Machine Translation. - Phil Blunsom; Trevor Cohn; Miles Osborne (ACL, 2008)

Probabilistic Inference for Machine Translation. - Phil Blunsom; Miles Osborne (EMNLP, 2008)

Bayesian Synchronous Grammar Induction. - Phil Blunsom; Trevor Cohn; Miles Osborne (NIPS, 2008)

A Gibbs Sampler for Phrasal Synchronous Grammar Induction. - Phil Blunsom; Trevor Cohn; Chris Dyer; Miles Osborne (ACL/IJCNLP, 2009)

A Note on the Implementation of Hierarchical Dirichlet Processes. - Phil Blunsom; Trevor Cohn; Sharon Goldwater; Mark Johnson 001 (ACL/IJCNLP (2), 2009)

Monte Carlo inference and maximization for phrase-based translation. - Abhishek Arun; Chris Dyer; Barry Haddow; Phil Blunsom; Adam Lopez; Philipp Koehn (CoNLL, 2009)

A Bayesian Model of Syntax-Directed Tree to String Grammar Induction. - Trevor Cohn; Phil Blunsom (EMNLP, 2009)

Inducing Compact but Accurate Tree-Substitution Grammars. - Trevor Cohn; Sharon Goldwater; Phil Blunsom (HLT-NAACL, 2009)

A Quantitative Analysis of Reordering Phenomena. - Alexandra Birch; Phil Blunsom; Miles Osborne (WMT@EACL, 2009)

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 - Phil Blunsom (Comput. Linguistics, 2009)

Blocked Inference in Bayesian Tree Substitution Grammars. - Trevor Cohn; Phil Blunsom (ACL (2), 2010)

cdec: A Decoder, Alignment, and Learning Framework for Finite-State and Context-Free Translation Models. - Chris Dyer; Adam Lopez; Juri Ganitkevitch; Jonathan Weese; Ferhan Türe; Phil Blunsom; Hendra Setiawan; Vladimir Eidelman; Philip Resnik (ACL (System Demonstrations), 2010)

Unsupervised Induction of Tree Substitution Grammars for Dependency Parsing. - Phil Blunsom; Trevor Cohn (EMNLP, 2010)

Inducing Synchronous Grammars with Slice Sampling. - Phil Blunsom; Trevor Cohn (HLT-NAACL, 2010)

Inducing Tree-Substitution Grammars. - Trevor Cohn; Phil Blunsom; Sharon Goldwater (J. Mach. Learn. Res., 2010)

Monte Carlo techniques for phrase-based translation. - Abhishek Arun; Barry Haddow; Philipp Koehn; Adam Lopez; Chris Dyer; Phil Blunsom (Mach. Transl., 2010)

Metrics for MT evaluation: evaluating reordering. - Alexandra Birch; Miles Osborne; Phil Blunsom (Mach. Transl., 2010)

A Hierarchical Pitman-Yor Process HMM for Unsupervised Part of Speech Induction. - Phil Blunsom; Trevor Cohn (ACL, 2011)

Bayesian Language Modelling of German Compounds. - Jan A. Botha; Chris Dyer; Phil Blunsom (COLING, 2012)

A Bayesian Model for Learning SCFGs with Discontiguous Rules. - Abby D. Levenberg; Chris Dyer; Phil Blunsom (EMNLP-CoNLL, 2012)

Unsupervised Bayesian Part of Speech Inference with Particle Gibbs. - Gregory Dubbin; Phil Blunsom (ECML/PKDD (1), 2012)

An Unsupervised Ranking Model for Noun-Noun Compositionality. - Karl Moritz Hermann; Phil Blunsom; Stephen Pulman (*SEM@NAACL-HLT, 2012)

Learning Semantics and Selectional Preference of Adjective-Noun Pairs. - Karl Moritz Hermann; Chris Dyer; Phil Blunsom; Stephen Pulman (*SEM@NAACL-HLT, 2012)

The Role of Syntax in Vector Space Models of Compositional Semantics. - Karl Moritz Hermann; Phil Blunsom (ACL (1), 2013)

"Not not bad" is not "bad": A distributional account of negation. - Karl Moritz Hermann; Edward Grefenstette; Phil Blunsom (CVSM@ACL, 2013)

Recurrent Convolutional Neural Networks for Discourse Compositionality. - Nal Kalchbrenner; Phil Blunsom (CVSM@ACL, 2013)

Collapsed Variational Bayesian Inference for Hidden Markov Models. - Pengyu Wang; Phil Blunsom (AISTATS, 2013)

Collapsed Variational Bayesian Inference for PCFGs. - Pengyu Wang; Phil Blunsom (CoNLL, 2013)

Adaptor Grammars for Learning Non-Concatenative Morphology. - Jan A. Botha; Phil Blunsom (EMNLP, 2013)

Recurrent Continuous Translation Models. - Nal Kalchbrenner; Phil Blunsom (EMNLP, 2013)

On Assessing the Accuracy of Positioning Systems in Indoor Environments. - Hongkai Wen 001; Zhuoling Xiao; Niki Trigoni; Phil Blunsom (EWSN, 2013)

A Systematic Bayesian Treatment of the IBM Alignment Models. - Yarin Gal; Phil Blunsom (HLT-NAACL, 2013)

Identification and mitigation of non-line-of-sight conditions using received signal strength. - Zhuoling Xiao; Hongkai Wen 001; Andrew Markham; Niki Trigoni; Phil Blunsom; Jeff Frolik (WiMob, 2013)

New Directions in Vector Space Models of Meaning. - Edward Grefenstette; Karl Moritz Hermann; Georgiana Dinu; Phil Blunsom (ACL (Tutorial Abstracts), 2014)

Multilingual Models for Compositional Distributed Semantics. - Karl Moritz Hermann; Phil Blunsom (ACL (1), 2014)

A Convolutional Neural Network for Modelling Sentences. - Nal Kalchbrenner; Edward Grefenstette; Phil Blunsom (ACL (1), 2014)

Learning Bilingual Word Representations by Marginalizing Alignments. - Tomás Kociský; Karl Moritz Hermann; Phil Blunsom (ACL (2), 2014)

Modelling the Lexicon in Unsupervised Part of Speech Induction. - Gregory Dubbin; Phil Blunsom (EACL, 2014)

Dynamic Topic Adaptation for Phrase-based MT. - Eva Hasler; Phil Blunsom; Philipp Koehn; Barry Haddow (EACL, 2014)

Compositional Morphology for Word Representations and Language Modelling. - Jan A. Botha; Phil Blunsom (ICML, 2014)

Linguistic steganography on Twitter: hierarchical language modeling with manual interaction. - Alex Wilson 001; Phil Blunsom; Andrew D. Ker (Media Watermarking, Security, and Forensics, 2014)

Modelling, Visualising and Summarising Documents with a Single Convolutional Neural Network. - Misha Denil; Alban Demiraj; Nal Kalchbrenner; Phil Blunsom; Nando de Freitas (CoRR, 2014)

A Deep Architecture for Semantic Parsing. - Edward Grefenstette; Phil Blunsom; Nando de Freitas; Karl Moritz Hermann (CoRR, 2014)

A Simple Model for Learning Multilingual Compositional Semantics. - Karl Moritz Hermann; Phil Blunsom (ICLR, 2014)

Deep Multi-Instance Transfer Learning. - Dimitrios Kotzias; Misha Denil; Phil Blunsom; Nando de Freitas (CoRR, 2014)

Bayesian Optimisation for Machine Translation. - Yishu Miao; Ziyu Wang 001; Phil Blunsom (CoRR, 2014)

Deep Learning for Answer Sentence Selection. - Lei Yu 008; Karl Moritz Hermann; Phil Blunsom; Stephen Pulman (CoRR, 2014)

A Fast and Simple Online Synchronous Context Free Grammar Extractor. - Paul Baltescu; Phil Blunsom (Prague Bull. Math. Linguistics, 2014)

OxLM: A Neural Language Modelling Framework for Machine Translation. - Paul Baltescu; Phil Blunsom; Hieu Hoang (Prague Bull. Math. Linguistics, 2014)

Tree Transduction Tools for cdec. - Austin Matthews; Paul Baltescu; Phil Blunsom; Alon Lavie; Chris Dyer (Prague Bull. Math. Linguistics, 2014)

Generative Incremental Dependency Parsing with Neural Networks. - Jan Buys; Phil Blunsom (ACL (2), 2015)

A Bayesian Model for Generative Transition-based Dependency Parsing. - Jan Buys; Phil Blunsom (DepLing, 2015)

Detection of Steganographic Techniques on Twitter. - Alex Wilson 001; Phil Blunsom; Andrew D. Ker (EMNLP, 2015)

Pragmatic Neural Language Modelling in Machine Translation. - Paul Baltescu; Phil Blunsom (HLT-NAACL, 2015)

Learning to Transduce with Unbounded Memory. - Edward Grefenstette; Karl Moritz Hermann; Mustafa Suleyman; Phil Blunsom (NIPS, 2015)

Teaching Machines to Read and Comprehend. - Karl Moritz Hermann; Tomás Kociský; Edward Grefenstette; Lasse Espeholt; Will Kay; Mustafa Suleyman; Phil Blunsom (NIPS, 2015)

Non-Line-of-Sight Identification and Mitigation Using Received Signal Strength. - Zhuoling Xiao; Hongkai Wen 001; Andrew Markham; Niki Trigoni; Phil Blunsom; Jeff Frolik (IEEE Trans. Wirel. Commun., 2015)

Latent Predictor Networks for Code Generation. - Wang Ling; Phil Blunsom; Edward Grefenstette; Karl Moritz Hermann; Tomás Kociský; Fumin Wang; Andrew W. Senior (ACL (1), 2016)

Semantic Parsing with Semi-Supervised Sequential Autoencoders. - Tomás Kociský; Gábor Melis; Edward Grefenstette; Chris Dyer; Wang Ling; Phil Blunsom; Karl Moritz Hermann (EMNLP, 2016)

Language as a Latent Variable: Discrete Generative Models for Sentence Compression. - Yishu Miao; Phil Blunsom (EMNLP, 2016)

Online Segment to Segment Neural Transduction. - Lei Yu 008; Jan Buys; Phil Blunsom (EMNLP, 2016)

Neural Variational Inference for Text Processing. - Yishu Miao; Lei Yu 008; Phil Blunsom (ICML, 2016)

Optimizing Performance of Recurrent Neural Networks on GPUs. - Jeremy Appleyard; Tomás Kociský; Phil Blunsom (CoRR, 2016)

Reasoning about Entailment with Neural Attention. - Tim Rocktäschel; Edward Grefenstette; Karl Moritz Hermann; Tomás Kociský; Phil Blunsom (ICLR (Poster), 2016)

Hybrid computing using a neural network with dynamic external memory. - 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; et al. (Nat., 2016)

Robust Incremental Neural Semantic Graph Parsing. - Jan Buys; Phil Blunsom (ACL (1), 2017)

Learning to Create and Reuse Words in Open-Vocabulary Neural Language Modeling. - Kazuya Kawakami; Chris Dyer; Phil Blunsom (ACL (1), 2017)

Program Induction by Rationale Generation: Learning to Solve and Explain Algebraic Word Problems. - Wang Ling; Dani Yogatama; Chris Dyer; Phil Blunsom (ACL (1), 2017)

Reference-Aware Language Models. - Zichao Yang; Phil Blunsom; Chris Dyer; Wang Ling (EMNLP, 2017)

Learning to Compose Words into Sentences with Reinforcement Learning. - Dani Yogatama; Phil Blunsom; Chris Dyer; Edward Grefenstette; Wang Ling (ICLR (Poster), 2017)

The Neural Noisy Channel. - Lei Yu 008; Phil Blunsom; Chris Dyer; Edward Grefenstette; Tomás Kociský (ICLR (Poster), 2017)

Discovering Discrete Latent Topics with Neural Variational Inference. - Yishu Miao; Edward Grefenstette; Phil Blunsom (ICML, 2017)

Latent Intention Dialogue Models. - Tsung-Hsien Wen; Yishu Miao; Phil Blunsom; Steve J. Young (ICML, 2017)

Oxford at SemEval-2017 Task 9: Neural AMR Parsing with Pointer-Augmented Attention. - Jan Buys; Phil Blunsom (SemEval@ACL, 2017)

Grounded Language Learning in a Simulated 3D World. - Karl Moritz Hermann; Felix Hill; Simon Green; Fumin Wang; Ryan Faulkner 001; Hubert Soyer; David Szepesvari; Wojciech Marian Czarnecki; Max Jaderberg; Denis Teplyashin; Marcus Wainwright; Chris Apps; et al. (CoRR, 2017)

Generative and Discriminative Text Classification with Recurrent Neural Networks. - Dani Yogatama; Chris Dyer; Wang Ling; Phil Blunsom (CoRR, 2017)

Understanding Grounded Language Learning Agents. - Felix Hill; Karl Moritz Hermann; Phil Blunsom; Stephen Clark (CoRR, 2017)

From Characters to Understanding Natural Language (C2NLU): Robust End-to-End Deep Learning for NLP (Dagstuhl Seminar 17042). - Phil Blunsom; Kyunghyun Cho; Chris Dyer; Hinrich Schütze (Dagstuhl Reports, 2017)

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 (ACL (1), 2018)

On the State of the Art of Evaluation in Neural Language Models. - Gábor Melis; Chris Dyer; Phil Blunsom (ICLR (Poster), 2018)

Memory Architectures in Recurrent Neural Network Language Models. - Dani Yogatama; Yishu Miao; Gábor Melis; Wang Ling; Adhiguna Kuncoro; Chris Dyer; Phil Blunsom (ICLR (Poster), 2018)

Neural Syntactic Generative Models with Exact Marginalization. - Jan Buys; Phil Blunsom (NAACL-HLT, 2018)

e-SNLI: Natural Language Inference with Natural Language Explanations. - Oana-Maria Camburu; Tim Rocktäschel; Thomas Lukasiewicz; Phil Blunsom (NeurIPS, 2018)

Neural Arithmetic Logic Units. - Andrew Trask; Felix Hill; Scott E. Reed; Jack W. Rae; Chris Dyer; Phil Blunsom (NeurIPS, 2018)

Pushing the bounds of dropout. - Gábor Melis; Charles Blundell; Tomás Kociský; Karl Moritz Hermann; Chris Dyer; Phil Blunsom (CoRR, 2018)

Encoding Spatial Relations from Natural Language. - Tiago Ramalho; Tomás Kociský; Frederic Besse; S. M. Ali Eslami; Gábor Melis; Fabio Viola; Phil Blunsom; Karl Moritz Hermann (CoRR, 2018)

Transferring Physical Motion Between Domains for Neural Inertial Tracking. - Changhao Chen; Yishu Miao; Chris Xiaoxuan Lu; Phil Blunsom; Andrew Markham; Niki Trigoni (CoRR, 2018)

Unsupervised Word Discovery with Segmental Neural Language Models. - Kazuya Kawakami; Chris Dyer; Phil Blunsom (CoRR, 2018)

Sentence Encoding with Tree-constrained Relation Networks. - Lei Yu 008; Cyprien de Masson d'Autume; Chris Dyer; Phil Blunsom; Lingpeng Kong; Wang Ling (CoRR, 2018)

Learning with Stochastic Guidance for Navigation. - Linhai Xie; Yishu Miao; Sen Wang 002; Phil Blunsom; Zhihua Wang 005; Changhao Chen; Andrew Markham; Niki Trigoni (CoRR, 2018)

The NarrativeQA Reading Comprehension Challenge. - Tomás Kociský; Jonathan Schwarz; Phil Blunsom; Chris Dyer; Karl Moritz Hermann; Gábor Melis; Edward Grefenstette (Trans. Assoc. Comput. Linguistics, 2018)

MotionTransformer: Transferring Neural Inertial Tracking between Domains. - Changhao Chen; Yishu Miao; Chris Xiaoxuan Lu; Linhai Xie; Phil Blunsom; Andrew Markham; Niki Trigoni (AAAI, 2019)

Learning to Discover, Ground and Use Words with Segmental Neural Language Models. - Kazuya Kawakami; Chris Dyer; Phil Blunsom (ACL (1), 2019)

Scalable Syntax-Aware Language Models Using Knowledge Distillation. - Adhiguna Kuncoro; Chris Dyer; Laura Rimell; Stephen Clark; Phil Blunsom (ACL (1), 2019)

WikiCREM: A Large Unsupervised Corpus for Coreference Resolution. - Vid Kocijan; Oana-Maria Camburu; Ana-Maria Cretu 002; Yordan Yordanov; Phil Blunsom; Thomas Lukasiewicz (EMNLP/IJCNLP (1), 2019)

Learning and Evaluating General Linguistic Intelligence. - Dani Yogatama; Cyprien de Masson d'Autume; Jerome T. Connor; Tomás Kociský; Mike Chrzanowski; Lingpeng Kong; Angeliki Lazaridou; Wang Ling; Lei Yu 008; Chris Dyer; Phil Blunsom (CoRR, 2019)

A Critical Analysis of Biased Parsers in Unsupervised Parsing. - Chris Dyer; Gábor Melis; Phil Blunsom (CoRR, 2019)

Putting Machine Translation in Context with the Noisy Channel Model. - Lei Yu 008; Laurent Sartran; Wojciech Stokowiec; Wang Ling; Lingpeng Kong; Phil Blunsom; Chris Dyer (CoRR, 2019)

Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods. - Oana-Maria Camburu; Eleonora Giunchiglia; Jakob N. Foerster; Thomas Lukasiewicz; Phil Blunsom (CoRR, 2019)

Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations. - Oana-Maria Camburu; Brendan Shillingford; Pasquale Minervini; Thomas Lukasiewicz; Phil Blunsom (ACL, 2020)

Learning to Segment Actions from Observation and Narration. - Daniel Fried; Jean-Baptiste Alayrac; Phil Blunsom; Chris Dyer; Stephen Clark; Aida Nematzadeh (ACL, 2020)

Simulating Early Word Learning in Situated Connectionist Agents. - Felix Hill; Stephen Clark; Phil Blunsom; Karl Moritz Hermann (CogSci, 2020)

Visual Grounding in Video for Unsupervised Word Translation. - Gunnar A. Sigurdsson; Jean-Baptiste Alayrac; Aida Nematzadeh; Lucas Smaira; Mateusz Malinowski; João Carreira 001; Phil Blunsom; Andrew Zisserman (CVPR, 2020)

Learning Robust and Multilingual Speech Representations. - Kazuya Kawakami; Luyu Wang; Chris Dyer; Phil Blunsom; Aäron van den Oord (EMNLP (Findings), 2020)

Mogrifier LSTM. - Gábor Melis; Tomás Kociský; Phil Blunsom (ICLR, 2020)

The DeepMind Chinese-English Document Translation System at WMT2020. - Lei Yu 008; Laurent Sartran; Po-Sen Huang; Wojciech Stokowiec; Domenic Donato; Srivatsan Srinivasan; Alek Andreev; Wang Ling; Sona Mokrá; Agustin Dal Lago; Yotam Doron; Susannah Young; et al. (WMT@EMNLP, 2020)

A Survey on Contextual Embeddings. - Qi Liu 049; Matt J. Kusner; Phil Blunsom (CoRR, 2020)

The Struggles of Feature-Based Explanations: Shapley Values vs. Minimal Sufficient Subsets. - Oana-Maria Camburu; Eleonora Giunchiglia; Jakob N. Foerster; Thomas Lukasiewicz; Phil Blunsom (CoRR, 2020)

Mutual Information Constraints for Monte-Carlo Objectives. - Gábor Melis; András György 001; Phil Blunsom (CoRR, 2020)

Syntactic Structure Distillation Pretraining for Bidirectional Encoders. - Adhiguna Kuncoro; Lingpeng Kong; Daniel Fried; Dani Yogatama; Laura Rimell; Chris Dyer; Phil Blunsom (Trans. Assoc. Comput. Linguistics, 2020)

Better Document-Level Machine Translation with Bayes' Rule. - Lei Yu 008; Laurent Sartran; Wojciech Stokowiec; Wang Ling; Lingpeng Kong; Phil Blunsom; Chris Dyer (Trans. Assoc. Comput. Linguistics, 2020)

A Generative Framework for Simultaneous Machine Translation. - Yishu Miao; Phil Blunsom; Lucia Specia (EMNLP (1), 2021)

Counterfactual Data Augmentation for Neural Machine Translation. - Qi Liu 049; Matt J. Kusner; Phil Blunsom (NAACL-HLT, 2021)

Mind the Gap: Assessing Temporal Generalization in Neural Language Models. - 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; et al. (NeurIPS, 2021)

Pitfalls of Static Language Modelling. - 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; et al. (CoRR, 2021)

A Systematic Investigation of Commonsense Understanding in Large Language Models. - Xiang Lorraine Li; Adhiguna Kuncoro; Cyprien de Masson d'Autume; Phil Blunsom; Aida Nematzadeh (CoRR, 2021)

Pretraining the Noisy Channel Model for Task-Oriented Dialogue. - Qi Liu 049; Lei Yu 008; Laura Rimell; Phil Blunsom (Trans. Assoc. Comput. Linguistics, 2021)

Learning With Stochastic Guidance for Robot Navigation. - Linhai Xie; Yishu Miao; Sen Wang 002; Phil Blunsom; Zhihua Wang 005; Changhao Chen; Andrew Markham; Niki Trigoni (IEEE Trans. Neural Networks Learn. Syst., 2021)

Revisiting the Compositional Generalization Abilities of Neural Sequence Models. - Arkil Patel; Satwik Bhattamishra; Phil Blunsom; Navin Goyal (ACL (2), 2022)

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 (EMNLP, 2022)

Augmenting Multi-Turn Text-to-SQL Datasets with Self-Play. - Qi Liu 049; Zihuiwen Ye; Tao Yu; Linfeng Song; Phil Blunsom (EMNLP (Findings), 2022)

StreamingQA: A Benchmark for Adaptation to New Knowledge over Time in Question Answering Models. - 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; et al. (ICML, 2022)

Learning Proof Path Selection Policies in Neural Theorem Proving. - Matthew Morris; Pasquale Minervini; Phil Blunsom (NeSy, 2022)

Rethinking 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 (CoRR, 2022)

Mutual Information Constraints for Monte-Carlo Objectives to Prevent Posterior Collapse Especially in Language Modelling. - Gábor Melis; András György 001; Phil Blunsom (J. Mach. Learn. Res., 2022)

Relational Memory-Augmented Language Models. - Qi Liu 049; Dani Yogatama; Phil Blunsom (Trans. Assoc. Comput. Linguistics, 2022)

Transformer Grammars: Augmenting Transformer Language Models with Syntactic Inductive Biases at Scale. - Laurent Sartran; Samuel Barrett; Adhiguna Kuncoro; Milos Stanojevic; Phil Blunsom; Chris Dyer (Trans. Assoc. Comput. Linguistics, 2022)

Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions. - Satwik Bhattamishra; Arkil Patel; Varun Kanade; Phil Blunsom (ACL (1), 2023)

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 (ACL (1), 2023)

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 (EACL (Findings), 2023)

Can Text Encoders be Deceived by Length Attack? - Chenghao Xiao; Zihuiwen Ye; G. Thomas Hudson; Zhongtian Sun; Phil Blunsom; Noura Al Moubayed (Tiny Papers @ ICLR, 2023)

Intriguing Properties of Quantization at Scale. - Arash Ahmadian; Saurabh Dash; Hongyu Chen 008; Bharat Venkitesh; Stephen Zhen Gou; Phil Blunsom; Ahmet Üstün; Sara Hooker (NeurIPS, 2023)

Intriguing Properties of Quantization at Scale. - Arash Ahmadian; Saurabh Dash; Hongyu Chen 008; Bharat Venkitesh; Stephen Gou; Phil Blunsom; Ahmet Üstün; Sara Hooker (CoRR, 2023)

Structural Transfer Learning in NL-to-Bash Semantic Parsers. - Kyle Duffy; Satwik Bhattamishra; Phil Blunsom (CoRR, 2023)

Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model. - 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; et al. (ACL (1), 2024)

Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions. - Satwik Bhattamishra; Arkil Patel; Phil Blunsom; Varun Kanade (ICLR, 2024)

Human Feedback is not Gold Standard. - Tom Hosking; Phil Blunsom; Max Bartolo (ICLR, 2024)

Separations in the Representational Capabilities of Transformers and Recurrent Architectures. - Satwik Bhattamishra; Michael Hahn 001; Phil Blunsom; Varun Kanade (NeurIPS, 2024)

BAM! Just Like That: Simple and Efficient Parameter Upcycling for Mixture of Experts. - Qizhen (Irene) Zhang; Nikolas Gritsch; Dwaraknath Gnaneshwar; Simon Guo 003; David Cairuz; Bharat Venkitesh; Jakob N. Foerster; Phil Blunsom; Sebastian Ruder; Ahmet Üstün; Acyr Locatelli (NeurIPS, 2024)

Aya 23: Open Weight Releases to Further Multilingual Progress. - 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; et al. (CoRR, 2024)

Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier. - John Dang; Shivalika Singh; Daniel D'souza; Arash Ahmadian; Alejandro Salamanca; Madeline Smith; Aidan Peppin; Sungjin Hong; Manoj Govindassamy; Terrence Zhao; Sandra Kublik; Meor Amer; et al. (CoRR, 2024)

Improving Reward Models with Synthetic Critiques. - Zihuiwen Ye; Fraser Greenlee-Scott; Max Bartolo; Phil Blunsom; Jon Ander Campos; Matthias Gallé (NAACL (Findings), 2025)

Rope to Nope and Back Again: A New Hybrid Attention Strategy. - Bowen Yang; Bharat Venkitesh; Dwarak Talupuru; Hangyu Lin; David Cairuz; Phil Blunsom; Acyr Locatelli (CoRR, 2025)

Uncertainty-Aware Step-wise Verification with Generative Reward Models. - Zihuiwen Ye; Luckeciano Carvalho Melo; Younesse Kaddar; Phil Blunsom; Sam Staton; Yarin Gal (CoRR, 2025)

Command A: An Enterprise-Ready Large Language Model. - Aakanksha; Arash Ahmadian; Marwan Ahmed; Jay Alammar; Milad Alizadeh; Yazeed Alnumay; Sophia Althammer; Arkady Arkhangorodsky; Viraat Aryabumi; Dennis Aumiller; Raphaël Avalos; Zahara Aviv; et al. (CoRR, 2025)

Aya Vision: Advancing the Frontier of Multilingual Multimodality. - Saurabh Dash; Yiyang Nan; John Dang; Arash Ahmadian; Shivalika Singh; Madeline Smith; Bharat Venkitesh; Vlad Shmyhlo; Viraat Aryabumi; Walter Beller-Morales; Jeremy Pekmez; Jason Ozuzu; et al. (CoRR, 2025)