Graph Based Translation Memory for Neural Machine Translation. - Mengzhou Xia; Guoping Huang; Lemao Liu; Shuming Shi 001 (AAAI, 2019)

Domain Adaptation of Neural Machine Translation by Lexicon Induction. - Junjie Hu 001; Mengzhou Xia; Graham Neubig; Jaime G. Carbonell (ACL (1), 2019)

Choosing Transfer Languages for Cross-Lingual Learning. - Yu-Hsiang Lin; Chian-Yu Chen; Jean Lee; Zirui Li; Yuyan Zhang; Mengzhou Xia; Shruti Rijhwani; Junxian He; Zhisong Zhang; Xuezhe Ma; Antonios Anastasopoulos; Patrick Littell; et al. (ACL (1), 2019)

Generalized Data Augmentation for Low-Resource Translation. - Mengzhou Xia; Xiang Kong; Antonios Anastasopoulos; Graham Neubig (ACL (1), 2019)

Demoting Racial Bias in Hate Speech Detection. - Mengzhou Xia; Anjalie Field; Yulia Tsvetkov (SocialNLP@ACL, 2020)

Predicting Performance for Natural Language Processing Tasks. - Mengzhou Xia; Antonios Anastasopoulos; Ruochen Xu; Yiming Yang; Graham Neubig (ACL, 2020)

A Summary of the First Workshop on Language Technology for Language Documentation and Revitalization. - Graham Neubig; Shruti Rijhwani; Alexis Palmer; Jordan MacKenzie; Hilaria Cruz; Xinjian Li; Matthew Lee 012; Aditi Chaudhary; Luke Gessler; Steven Abney; Shirley Anugrah Hayati; Antonios Anastasopoulos; et al. (SLTU-CCURL@LREC, 2020)

Non-Parametric Few-Shot Learning for Word Sense Disambiguation. - Howard Chen 003; Mengzhou Xia; Danqi Chen 001 (NAACL-HLT, 2021)

MetaXL: Meta Representation Transformation for Low-resource Cross-lingual Learning. - Mengzhou Xia; Guoqing Zheng; Subhabrata Mukherjee; Milad Shokouhi; Graham Neubig; Ahmed Hassan Awadallah (NAACL-HLT, 2021)

Structured Pruning Learns Compact and Accurate Models. - Mengzhou Xia; Zexuan Zhong; Danqi Chen 001 (ACL (1), 2022)

MABEL: Attenuating Gender Bias using Textual Entailment Data. - Jacqueline He; Mengzhou Xia; Christiane Fellbaum; Danqi Chen 001 (EMNLP, 2022)

Don't Prompt, Search! Mining-based Zero-Shot Learning with Language Models. - Mozes van de Kar; Mengzhou Xia; Danqi Chen 001; Mikel Artetxe (EMNLP, 2022)

Prompting ELECTRA: Few-Shot Learning with Discriminative Pre-Trained Models. - Mengzhou Xia; Mikel Artetxe; Jingfei Du; Danqi Chen 001; Veselin Stoyanov (EMNLP, 2022)

Training Trajectories of Language Models Across Scales. - Mengzhou Xia; Mikel Artetxe; Chunting Zhou; Xi Victoria Lin; Ramakanth Pasunuru; Danqi Chen 001; Luke Zettlemoyer; Veselin Stoyanov (ACL (1), 2023)

LitSearch: A Retrieval Benchmark for Scientific Literature Search. - Anirudh Ajith; Mengzhou Xia; Alexis Chevalier; Tanya Goyal; Danqi Chen 001; Tianyu Gao 001 (EMNLP, 2024)

Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation. - Yangsibo Huang; Samyak Gupta; Mengzhou Xia; Kai Li 001; Danqi Chen 001 (ICLR, 2024)

Detecting Pretraining Data from Large Language Models. - Weijia Shi; Anirudh Ajith; Mengzhou Xia; Yangsibo Huang; Daogao Liu; Terra Blevins; Danqi Chen 001; Luke Zettlemoyer (ICLR, 2024)

Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning. - Mengzhou Xia; Tianyu Gao 001; Zhiyuan Zeng; Danqi Chen 001 (ICLR, 2024)

Language Models as Science Tutors. - Alexis Chevalier; Jiayi Geng; Alexander Wettig; Howard Chen 003; Sebastian Mizera; Toni Annala; Max Jameson Aragon; Arturo Rodríguez Fanlo; Simon Frieder; Simon Machado; Akshara Prabhakar; Ellie Thieu; et al. (ICML, 2024)

Trainable Transformer in Transformer. - Abhishek Panigrahi; Sadhika Malladi; Mengzhou Xia; Sanjeev Arora (ICML, 2024)

Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications. - Boyi Wei; Kaixuan Huang; Yangsibo Huang; Tinghao Xie; Xiangyu Qi; Mengzhou Xia; Prateek Mittal; Mengdi Wang; Peter Henderson 002 (ICML, 2024)

LESS: Selecting Influential Data for Targeted Instruction Tuning. - Mengzhou Xia; Sadhika Malladi; Suchin Gururangan; Sanjeev Arora; Danqi Chen 001 (ICML, 2024)

InstructEval: Systematic Evaluation of Instruction Selection Methods. - Anirudh Ajith; Chris Pan; Mengzhou Xia; Ameet Deshpande; Karthik Narasimhan (NAACL-HLT (Findings), 2024)

SimPO: Simple Preference Optimization with a Reference-Free Reward. - Yu Meng 001; Mengzhou Xia; Danqi Chen 001 (NeurIPS, 2024)

CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs. - Zirui Wang; Mengzhou Xia; Luxi He; Howard Chen 003; Yitao Liu; Richard Zhu; Kaiqu Liang; Xindi Wu; Haotian Liu; Sadhika Malladi; Alexis Chevalier; Sanjeev Arora; et al. (NeurIPS, 2024)

Language Models as Science Tutors. - Alexis Chevalier; Jiayi Geng; Alexander Wettig; Howard Chen 003; Sebastian Mizera; Toni Annala; Max Jameson Aragon; Arturo Rodríguez Fanlo; Simon Frieder; Simon Machado; Akshara Prabhakar; Ellie Thieu; et al. (CoRR, 2024)

What's in Your "Safe" Data?: Identifying Benign Data that Breaks Safety. - Luxi He; Mengzhou Xia; Peter Henderson 002 (CoRR, 2024)

Lory: Fully Differentiable Mixture-of-Experts for Autoregressive Language Model Pre-training. - Zexuan Zhong; Mengzhou Xia; Danqi Chen 001; Mike Lewis (CoRR, 2024)

BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval. - Hongjin Su; Howard Yen; Mengzhou Xia; Weijia Shi; Niklas Muennighoff; Han-yu Wang; Haisu Liu; Quan Shi; Zachary S. Siegel; Michael Tang; Ruoxi Sun 002; Jinsung Yoon; et al. (ICLR, 2025)

ICONS: Influence Consensus for Vision-Language Data Selection. - Xindi Wu; Mengzhou Xia; Rulin Shao; Zhiwei Deng; Pang Wei Koh; Olga Russakovsky (CoRR, 2025)

Rethinking Mixture-of-Agents: Is Mixing Different Large Language Models Beneficial? - Wenzhe Li; Yong Lin; Mengzhou Xia; Chi Jin (CoRR, 2025)

PDE-Controller: LLMs for Autoformalization and Reasoning of PDEs. - Mauricio Soroco; Jialin Song; Mengzhou Xia; Kye Emond; Weiran Sun; Wuyang Chen 001 (CoRR, 2025)

Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving. - Yong Lin; Shange Tang; Bohan Lyu 001; Jiayun Wu; Hongzhou Lin; Kaiyu Yang; Jia Li; Mengzhou Xia; Danqi Chen 001; Sanjeev Arora; Chi Jin 001 (CoRR, 2025)

MMTEB: Massive Multilingual Text Embedding Benchmark. - Kenneth C. Enevoldsen; Isaac Chung; Imene Kerboua; Márton Kardos; Ashwin Mathur; David Stap; Jay Gala; Wissam Siblini; Dominik Krzeminski; Genta Indra Winata; Saba Sturua; Saiteja Utpala; et al. (CoRR, 2025)

MoDoMoDo: Multi-Domain Data Mixtures for Multimodal LLM Reinforcement Learning. - Yiqing Liang; Jielin Qiu; Wenhao Ding; Zuxin Liu; James Tompkin 001; Mengdi Xu; Mengzhou Xia; Zhengzhong Tu; Laixi Shi; Jiacheng Zhu (CoRR, 2025)

The Surprising Effectiveness of Negative Reinforcement in LLM Reasoning. - Xinyu Zhu; Mengzhou Xia; Zhepei Wei; Wei-Lin Chen; Danqi Chen 001; Yu Meng 001 (CoRR, 2025)