Multilingual Spectral Clustering Using Document Similarity Propagation. - Dani Yogatama; Kumiko Tanaka-Ishii (EMNLP, 2009)

Part-of-Speech Tagging for Twitter: Annotation, Features, and Experiments. - Kevin Gimpel; Nathan Schneider 001; Brendan O'Connor 001; Dipanjan Das 001; Daniel Mills; Jacob Eisenstein; Michael Heilman; Dani Yogatama; Jeffrey Flanigan; Noah A. Smith (ACL (2), 2011)

Predicting a Scientific Community's Response to an Article. - Dani Yogatama; Michael Heilman; Brendan O'Connor 001; Chris Dyer; Bryan R. Routledge; Noah A. Smith (EMNLP, 2011)

A Probabilistic Model for Canonicalizing Named Entity Mentions. - Dani Yogatama; Yanchuan Sim; Noah A. Smith (ACL (1), 2012)

A Penny for Your Tweets: Campaign Contributions and Capitol Hill Microblogs. - Tae Yano; Dani Yogatama; Noah A. Smith (ICWSM, 2013)

A Sparse and Adaptive Prior for Time-Dependent Model Parameters. - Dani Yogatama; Bryan R. Routledge; Noah A. Smith (CoRR, 2013)

Linguistic Structured Sparsity in Text Categorization. - Dani Yogatama; Noah A. Smith (ACL (1), 2014)

Efficient Transfer Learning Method for Automatic Hyperparameter Tuning. - Dani Yogatama; Gideon Mann (AISTATS, 2014)

Making the Most of Bag of Words: Sentence Regularization with Alternating Direction Method of Multipliers. - Dani Yogatama; Noah A. Smith (ICML, 2014)

Dynamic Language Models for Streaming Text. - Dani Yogatama; Chong Wang 002; Bryan R. Routledge; Noah A. Smith; Eric P. Xing (Trans. Assoc. Comput. Linguistics, 2014)

Sparse Overcomplete Word Vector Representations. - Manaal Faruqui; Yulia Tsvetkov; Dani Yogatama; Chris Dyer; Noah A. Smith (ACL (1), 2015)

Embedding Methods for Fine Grained Entity Type Classification. - Dani Yogatama; Daniel Gillick; Nevena Lazic (ACL (2), 2015)

Extractive Summarization by Maximizing Semantic Volume. - Dani Yogatama; Fei Liu 004; Noah A. Smith (EMNLP, 2015)

Bayesian Optimization of Text Representations. - Dani Yogatama; Lingpeng Kong; Noah A. Smith (EMNLP, 2015)

Learning Word Representations with Hierarchical Sparse Coding. - Dani Yogatama; Manaal Faruqui; Chris Dyer; Noah A. Smith (ICML, 2015)

Deep Speech 2: End-to-End Speech Recognition in English and Mandarin. - Dario Amodei; Rishita Anubhai; Eric Battenberg; Carl Case; Jared Casper; Bryan Catanzaro; Jingdong Chen; Mike Chrzanowski; Adam Coates 002; Greg Diamos; Erich Elsen; Jesse H. Engel; et al. (CoRR, 2015)

Bayesian Optimization of Text Representations. - Dani Yogatama; Noah A. Smith (CoRR, 2015)

Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin. - Dario Amodei; Sundaram Ananthanarayanan; Rishita Anubhai; Jingliang Bai; Eric Battenberg; Carl Case; Jared Casper; Bryan Catanzaro; Jingdong Chen; Mike Chrzanowski; Adam Coates 002; Greg Diamos; et al. (ICML, 2016)

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

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

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

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)

Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation. - Po-Sen Huang; Robert Stanforth; Johannes Welbl; Chris Dyer; Dani Yogatama; Sven Gowal; Krishnamurthy Dvijotham; Pushmeet Kohli (EMNLP/IJCNLP (1), 2019)

Variational Smoothing in Recurrent Neural Network Language Models. - Lingpeng Kong; Gábor Melis; Wang Ling; Lei Yu 008; Dani Yogatama (ICLR (Poster), 2019)

Episodic Memory in Lifelong Language Learning. - Cyprien de Masson d'Autume; Sebastian Ruder; Lingpeng Kong; Dani Yogatama (NeurIPS, 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)

Grandmaster level in StarCraft II using multi-agent reinforcement learning. - Oriol Vinyals; Igor Babuschkin; Wojciech M. Czarnecki; Michaël Mathieu; Andrew Dudzik; Junyoung Chung; David H. Choi; Richard Powell; Timo Ewalds; Petko Georgiev; Junhyuk Oh; Dan Horgan; et al. (Nat., 2019)

Jointly learning sentence embeddings and syntax with unsupervised Tree-LSTMs. - Jean Maillard; Stephen Clark; Dani Yogatama (Nat. Lang. Eng., 2019)

On the Cross-lingual Transferability of Monolingual Representations. - Mikel Artetxe; Sebastian Ruder; Dani Yogatama (ACL, 2020)

A Call for More Rigor in Unsupervised Cross-lingual Learning. - Mikel Artetxe; Sebastian Ruder; Dani Yogatama; Gorka Labaka; Eneko Agirre (ACL, 2020)

Reducing Sentiment Bias in Language Models via Counterfactual Evaluation. - Po-Sen Huang; Huan Zhang; Ray Jiang; Robert Stanforth; Johannes Welbl; Jack Rae; Vishal Maini; Dani Yogatama; Pushmeet Kohli (EMNLP (Findings), 2020)

A Mutual Information Maximization Perspective of Language Representation Learning. - Lingpeng Kong; Cyprien de Masson d'Autume; Lei Yu 008; Wang Ling; Zihang Dai; Dani Yogatama (ICLR, 2020)

Modelling Latent Skills for Multitask Language Generation. - Kris Cao; Dani Yogatama (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)

Finetuning Pretrained Transformers into RNNs. - Jungo Kasai; Hao Peng 009; Yizhe Zhang 002; Dani Yogatama; Gabriel Ilharco; Nikolaos Pappas 002; Yi Mao; Weizhu Chen; Noah A. Smith (EMNLP (1), 2021)

Random Feature Attention. - Hao Peng 009; Nikolaos Pappas 002; Dani Yogatama; Roy Schwartz 001; Noah A. Smith; Lingpeng Kong (ICLR, 2021)

LiRo: Benchmark and leaderboard for Romanian language tasks. - Stefan Daniel Dumitrescu; Petru Rebeja; Beáta Lorincz; Mihaela Gaman; Andrei-Marius Avram; Mihai Ilie; Andrei Pruteanu; Adriana Stan; Lorena Rosia; Cristina Iacobescu; Luciana Morogan; George Dima; et al. (NeurIPS Datasets and Benchmarks, 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)

End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering. - Devendra Singh Sachan; Siva Reddy; William L. Hamilton; Chris Dyer; Dani Yogatama (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)

Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers. - Yi Tay; Mostafa Dehghani 001; Jinfeng Rao; William Fedus; Samira Abnar; Hyung Won Chung; Sharan Narang; Dani Yogatama; Ashish Vaswani; Donald Metzler (CoRR, 2021)

Balancing Average and Worst-case Accuracy in Multitask Learning. - Paul Michel; Sebastian Ruder; Dani Yogatama (CoRR, 2021)

Adaptive Semiparametric Language Models. - Dani Yogatama; Cyprien de Masson d'Autume; Lingpeng Kong (Trans. Assoc. Comput. Linguistics, 2021)

ABC: Attention with Bounded-memory Control. - Hao Peng 009; Jungo Kasai; Nikolaos Pappas 002; Dani Yogatama; Zhaofeng Wu; Lingpeng Kong; Roy Schwartz 001; Noah A. Smith (ACL (1), 2022)

Scale Efficiently: Insights from Pretraining and Finetuning Transformers. - Yi Tay; Mostafa Dehghani 001; Jinfeng Rao; William Fedus; Samira Abnar; Hyung Won Chung; Sharan Narang; Dani Yogatama; Ashish Vaswani; Donald Metzler (ICLR, 2022)

A Contrastive Framework for Neural Text Generation. - Yixuan Su; Tian Lan 003; Yan Wang 060; Dani Yogatama; Lingpeng Kong; Nigel Collier (NeurIPS, 2022)

HighMMT: Towards Modality and Task Generalization for High-Modality Representation Learning. - Paul Pu Liang; Yiwei Lyu; Xiang Fan; Shentong Mo; Dani Yogatama; Louis-Philippe Morency; Ruslan Salakhutdinov (CoRR, 2022)

Language Models Can See: Plugging Visual Controls in Text Generation. - Yixuan Su; Tian Lan 003; Yahui Liu; Fangyu Liu 001; Dani Yogatama; Yan Wang 060; Lingpeng Kong; Nigel Collier (CoRR, 2022)

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

Emergent Abilities of Large Language Models. - Jason Wei; Yi Tay; Rishi Bommasani; Colin Raffel; Barret Zoph; Sebastian Borgeaud; Dani Yogatama; Maarten Bosma; Denny Zhou; Donald Metzler; Ed H. Chi; Tatsunori Hashimoto; et al. (Trans. Mach. Learn. Res., 2022)

The Distributional Hypothesis Does Not Fully Explain the Benefits of Masked Language Model Pretraining. - Ting-Rui Chiang; Dani Yogatama (EMNLP, 2023)

Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling? - Yi Tay; Mostafa Dehghani 001; Samira Abnar; Hyung Won Chung; William Fedus; Jinfeng Rao; Sharan Narang; Vinh Q. Tran 002; Dani Yogatama; Donald Metzler (EMNLP (Findings), 2023)

Questions Are All You Need to Train a Dense Passage Retriever. - Devendra Singh Sachan; Mike Lewis; Dani Yogatama; Luke Zettlemoyer; Joelle Pineau; Manzil Zaheer (Trans. Assoc. Comput. Linguistics, 2023)

High-Modality Multimodal Transformer: Quantifying Modality & Interaction Heterogeneity for High-Modality Representation Learning. - Paul Pu Liang; Yiwei Lyu; Xiang Fan; Jeffrey Tsaw; Yudong Liu; Shentong Mo; Dani Yogatama; Louis-Philippe Morency; Russ Salakhutdinov (Trans. Mach. Learn. Res., 2023)

Interpretable Diffusion via Information Decomposition. - Xianghao Kong; Ollie Liu; Han Li; Dani Yogatama; Greg Ver Steeg (ICLR, 2024)

On Retrieval Augmentation and the Limitations of Language Model Training. - Ting-Rui Chiang; Xinyan Yu 001; Joshua Robinson; Ollie Liu; Isabelle Lee; Dani Yogatama (NAACL (Short Papers), 2024)

DeLLMa: A Framework for Decision Making Under Uncertainty with Large Language Models. - Ollie Liu; Deqing Fu; Dani Yogatama; Willie Neiswanger (CoRR, 2024)

Understanding In-Context Learning with a Pelican Soup Framework. - Ting-Rui Chiang; Dani Yogatama (CoRR, 2024)

IsoBench: Benchmarking Multimodal Foundation Models on Isomorphic Representations. - Deqing Fu; Ghazal Khalighinejad; Ollie Liu; Bhuwan Dhingra; Dani Yogatama; Robin Jia; Willie Neiswanger (CoRR, 2024)

Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models. - Aitor Ormazabal; Che Zheng; Cyprien de Masson d'Autume; Dani Yogatama; Deyu Fu; Donovan Ong; Eric Chen; Eugenie Lamprecht; Hai Pham; Isaac Ong; Kaloyan Aleksiev; Lei Li 039; et al. (CoRR, 2024)

Vibe-Eval: A hard evaluation suite for measuring progress of multimodal language models. - Piotr Padlewski; Max Bain; Matthew Henderson; Zhongkai Zhu; Nishant Relan; Hai Pham; Donovan Ong; Kaloyan Aleksiev; Aitor Ormazabal; Samuel Phua; Ethan Yeo; Eugenie Lamprecht; et al. (CoRR, 2024)

LocateBench: Evaluating the Locating Ability of Vision Language Models. - Ting-Rui Chiang; Joshua Robinson; Xinyan Velocity Yu; Dani Yogatama (CoRR, 2024)

Causal Interventions on Causal Paths: Mapping GPT-2's Reasoning From Syntax to Semantics. - Isabelle Lee; Joshua Lum; Ziyi Liu; Dani Yogatama (CoRR, 2024)

The Rotary Position Embedding May Cause Dimension Inefficiency in Attention Heads for Long-Distance Retrieval. - Ting-Rui Chiang; Dani Yogatama (ACL (Findings), 2025)

DeLLMa: Decision Making Under Uncertainty with Large Language Models. - Ollie Liu; Deqing Fu; Dani Yogatama; Willie Neiswanger (ICLR, 2025)

The Semantic Hub Hypothesis: Language Models Share Semantic Representations Across Languages and Modalities. - Zhaofeng Wu; Xinyan Velocity Yu; Dani Yogatama; Jiasen Lu; Yoon Kim (ICLR, 2025)

Ethical AI on the Waitlist: Group Fairness Evaluation of LLM-Aided Organ Allocation. - Hannah Murray; Brian Hyeongseok Kim; Isabelle Lee; Jason Byun; Dani Yogatama; Evi Micha (CoRR, 2025)

Textual Steering Vectors Can Improve Visual Understanding in Multimodal Large Language Models. - Woody Haosheng Gan; Deqing Fu; Julian Asilis; Ollie Liu; Dani Yogatama; Vatsal Sharan; Robin Jia; Willie Neiswanger (CoRR, 2025)

FOL-Pretrain: A complexity annotated corpus of first-order logic. - Isabelle Lee; Sarah Liaw; Dani Yogatama (CoRR, 2025)