Deep Multitask Learning for Semantic Dependency Parsing. - Hao Peng 009; Sam Thomson; Noah A. Smith (ACL (1), 2017)

Backpropagating through Structured Argmax using a SPIGOT. - Hao Peng 009; Sam Thomson; Noah A. Smith (ACL (1), 2018)

Rational Recurrences. - Hao Peng 009; Roy Schwartz 001; Sam Thomson; Noah A. Smith (EMNLP, 2018)

Learning Joint Semantic Parsers from Disjoint Data. - Hao Peng 009; Sam Thomson; Swabha Swayamdipta; Noah A. Smith (NAACL-HLT, 2018)

"You are no Jack Kennedy": On Media Selection of Highlights from Presidential Debates. - Chenhao Tan; Hao Peng 009; Noah A. Smith (WWW, 2018)

RNN Architecture Learning with Sparse Regularization. - Jesse Dodge; Roy Schwartz 001; Hao Peng 009; Noah A. Smith (EMNLP/IJCNLP (1), 2019)

PaLM: A Hybrid Parser and Language Model. - Hao Peng 009; Roy Schwartz 001; Noah A. Smith (EMNLP/IJCNLP (1), 2019)

A Mixture of h - 1 Heads is Better than h Heads. - Hao Peng 009; Roy Schwartz 001; Dianqi Li; Noah A. Smith (ACL, 2020)

Deep Encoder, Shallow Decoder: Reevaluating the Speed-Quality Tradeoff in Machine Translation. - Jungo Kasai; Nikolaos Pappas 002; Hao Peng 009; James Cross 003; Noah A. Smith (CoRR, 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)

Deep Encoder, Shallow Decoder: Reevaluating Non-autoregressive Machine Translation. - Jungo Kasai; Nikolaos Pappas 002; Hao Peng 009; James Cross 003; Noah A. Smith (ICLR, 2021)

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

Contextualized Perturbation for Textual Adversarial Attack. - Dianqi Li; Yizhe Zhang 002; Hao Peng 009; Liqun Chen 001; Chris Brockett; Ming-Ting Sun; Bill Dolan (NAACL-HLT, 2021)

Infusing Finetuning with Semantic Dependencies. - Zhaofeng Wu; Hao Peng 009; Noah A. Smith (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)

Tailor: Generating and Perturbing Text with Semantic Controls. - Alexis Ross; Tongshuang Wu; Hao Peng 009; Matthew E. Peters; Matt Gardner 001 (ACL (1), 2022)

How Much Does Attention Actually Attend? Questioning the Importance of Attention in Pretrained Transformers. - Michael Hassid; Hao Peng 009; Daniel Rotem; Jungo Kasai; Ivan Montero; Noah A. Smith; Roy Schwartz 001 (EMNLP (Findings), 2022)

Twist Decoding: Diverse Generators Guide Each Other. - Jungo Kasai; Keisuke Sakaguchi; Ronan Le Bras 001; Hao Peng 009; Ximing Lu; Dragomir Radev; Yejin Choi 001; Noah A. Smith (EMNLP, 2022)

Modeling Context With Linear Attention for Scalable Document-Level Translation. - Zhaofeng Wu; Hao Peng 009; Nikolaos Pappas 002; Noah A. Smith (EMNLP (Findings), 2022)

Towards Efficient and Generalizable Natural Language Processing - Hao Peng 009 (2022)

Efficiency Pentathlon: A Standardized Arena for Efficiency Evaluation. - Hao Peng 009; Qingqing Cao; Jesse Dodge; Matthew E. Peters; Jared Fernandez; Tom Sherborne; Kyle Lo; Sam Skjonsberg; Emma Strubell; Darrell Plessas; Iz Beltagy; Evan Pete Walsh; et al. (CoRR, 2023)

FiLM: Fill-in Language Models for Any-Order Generation. - Tianxiao Shen; Hao Peng 009; Ruoqi Shen; Yao Fu; Zaïd Harchaoui; Yejin Choi 001 (CoRR, 2023)

Prudent Silence or Foolish Babble? Examining Large Language Models' Responses to the Unknown. - Genglin Liu; Xingyao Wang 002; Lifan Yuan; Yangyi Chen; Hao Peng 009 (CoRR, 2023)

Catwalk: A Unified Language Model Evaluation Framework for Many Datasets. - Dirk Groeneveld; Anas Awadalla; Iz Beltagy; Akshita Bhagia; Ian Magnusson; Hao Peng 009; Oyvind Tafjord; Pete Walsh; Kyle Richardson 001; Jesse Dodge (CoRR, 2023)

Transparency Helps Reveal When Language Models Learn Meaning. - Zhaofeng Wu; William Merrill; Hao Peng 009; Iz Beltagy; Noah A. Smith (Trans. Assoc. Comput. Linguistics, 2023)

ActionIE: Action Extraction from Scientific Literature with Programming Languages. - Xianrui Zhong; Yufeng Du; Siru Ouyang; Ming Zhong 005; Tingfeng Luo; Qirong Ho; Hao Peng 009; Heng Ji 001; Jiawei Han 001 (ACL (1), 2024)

Measuring and Improving Attentiveness to Partial Inputs with Counterfactuals. - Yanai Elazar; Bhargavi Paranjape; Hao Peng 009; Sarah Wiegreffe; Khyathi Raghavi Chandu; Vivek Srikumar; Sameer Singh 001; Noah A. Smith (EMNLP (Findings), 2024)

MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback. - Xingyao Wang 002; Zihan Wang 010; Jiateng Liu; Yangyi Chen; Lifan Yuan; Hao Peng 009; Heng Ji 001 (ICLR, 2024)

TRAM: Bridging Trust Regions and Sharpness Aware Minimization. - Tom Sherborne; Naomi Saphra; Pradeep Dasigi; Hao Peng 009 (ICLR, 2024)

CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets. - Lifan Yuan; Yangyi Chen; Xingyao Wang 002; Yi Fung 001; Hao Peng 009; Heng Ji 001 (ICLR, 2024)

Executable Code Actions Elicit Better LLM Agents. - Xingyao Wang 002; Yangyi Chen; Lifan Yuan; Yizhe Zhang 002; Yunzhu Li; Hao Peng 009; Heng Ji 001 (ICML, 2024)

Language Models Hallucinate, but May Excel at Fact Verification. - Jian Guan 002; Jesse Dodge; David Wadden; Minlie Huang; Hao Peng 009 (NAACL-HLT, 2024)

LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models. - Chi Han; Qifan Wang 001; Hao Peng 009; Wenhan Xiong; Yu Chen 022; Heng Ji 001; Sinong Wang (NAACL-HLT, 2024)

LETI: Learning to Generate from Textual Interactions. - Xingyao Wang 002; Hao Peng 009; Reyhaneh Jabbarvand; Heng Ji 001 (NAACL-HLT (Findings), 2024)

Source-Aware Training Enables Knowledge Attribution in Language Models. - Muhammad Khalifa; David Wadden; Emma Strubell; Honglak Lee; Lu Wang 008; Iz Beltagy; Hao Peng 009 (CoRR, 2024)

OpenDevin: An Open Platform for AI Software Developers as Generalist Agents. - Xingyao Wang 002; Boxuan Li; Yufan Song; Frank F. Xu; Xiangru Tang; Mingchen Zhuge; Jiayi Pan; Yueqi Song; Bowen Li 002; Jaskirat Singh; Hoang H. Tran; Fuqiang Li; et al. (CoRR, 2024)

FactCheckmate: Preemptively Detecting and Mitigating Hallucinations in LMs. - Deema Alnuhait; Neeraja Kirtane; Muhammad Khalifa; Hao Peng 009 (CoRR, 2024)

A Single Transformer for Scalable Vision-Language Modeling. - Yangyi Chen; Xingyao Wang 002; Hao Peng 009; Heng Ji 001 (Trans. Mach. Learn. Res., 2024)

A Little Goes a Long Way: Efficient Long Context Training and Inference with Partial Contexts. - Suyu Ge; Xihui Lin; Yunan Zhang 001; Jiawei Han 001; Hao Peng 009 (ICLR, 2025)

Scaling Diffusion Language Models via Adaptation from Autoregressive Models. - Shansan Gong; Shivam Agarwal; Yizhe Zhang 002; Jiacheng Ye; Lin Zheng; Mukai Li; Chenxin An; Peilin Zhao; Wei Bi; Jiawei Han 001; Hao Peng 009; Lingpeng Kong (ICLR, 2025)

Eliminating Position Bias of Language Models: A Mechanistic Approach. - Ziqi Wang 003; Hanlin Zhang 002; Xiner Li; Kuan-Hao Huang; Chi Han; Shuiwang Ji; Sham M. Kakade; Hao Peng 009; Heng Ji 001 (ICLR, 2025)

LLMs are Vulnerable to Malicious Prompts Disguised as Scientific Language. - Yubin Ge; Neeraja Kirtane; Hao Peng 009; Dilek Hakkani-Tür (CoRR, 2025)

Process Reward Models That Think. - Muhammad Khalifa; Rishabh Agarwal; Lajanugen Logeswaran; Jaekyeom Kim; Hao Peng 009; Moontae Lee; Honglak Lee; Lu Wang 008 (CoRR, 2025)

Reinforcement Learning Finetunes Small Subnetworks in Large Language Models. - Sagnik Mukherjee; Lifan Yuan; Dilek Hakkani-Tur; Hao Peng 009 (CoRR, 2025)

mCLM: A Function-Infused and Synthesis-Friendly Modular Chemical Language Model. - Carl Edwards; Chi Han; Gawon Lee; Thao Nguyen; Bowen Jin; Chetan Prasad; Sara Szymkuc; Bartosz A. Grzybowski; Ying Diao; Jiawei Han 001; Ge Liu; Hao Peng 009; et al. (CoRR, 2025)

The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning. - Shivam Agarwal; Zimin Zhang; Lifan Yuan; Jiawei Han 001; Hao Peng 009 (CoRR, 2025)