Deep Automated Multi-task Learning. - Davis Liang; Yan Shu (IJCNLP(2), 2017)

Automated Multi-task Learning. - Davis Liang (2017)

Learning Noise-Invariant Representations for Robust Speech Recognition. - Davis Liang; Zhiheng Huang; Zachary C. Lipton (SLT, 2018)

Pseudolikelihood Reranking with Masked Language Models. - Julian Salazar; Davis Liang; Toan Q. Nguyen; Katrin Kirchhoff (CoRR, 2019)

Masked Language Model Scoring. - Julian Salazar; Davis Liang; Toan Q. Nguyen; Katrin Kirchhoff (ACL, 2020)

Improve Transformer Models with Better Relative Position Embeddings. - Zhiheng Huang; Davis Liang; Peng Xu; Bing Xiang (EMNLP (Findings), 2020)

TRANS-BLSTM: Transformer with Bidirectional LSTM for Language Understanding. - Zhiheng Huang; Peng Xu; Davis Liang; Ajay Mishra; Bing Xiang (CoRR, 2020)

Embedding-based Zero-shot Retrieval through Query Generation. - Davis Liang; Peng Xu; Siamak Shakeri; Cícero Nogueira dos Santos; Ramesh Nallapati; Zhiheng Huang; Bing Xiang (CoRR, 2020)

Decoding and Diversity in Machine Translation. - Nicholas Roberts; Davis Liang; Graham Neubig; Zachary C. Lipton (CoRR, 2020)

Multiplicative Position-aware Transformer Models for Language Understanding. - Zhiheng Huang; Davis Liang; Peng Xu; Bing Xiang (CoRR, 2021)

Attention-guided Generative Models for Extractive Question Answering. - Peng Xu; Davis Liang; Zhiheng Huang; Bing Xiang (CoRR, 2021)

Adaptable Claim Rewriting with Offline Reinforcement Learning for Effective Misinformation Discovery. - Ashkan Kazemi; Artem Abzaliev; Naihao Deng; Rui Hou 007; Davis Liang; Scott A. Hale; Verónica Pérez-Rosas; Rada Mihalcea (CoRR, 2022)

A Study on Knowledge Distillation from Weak Teacher for Scaling Up Pre-trained Language Models. - Hayeon Lee; Rui Hou 007; Jongpil Kim; Davis Liang; Sung Ju Hwang; Alexander Min (ACL (Findings), 2023)

Generating Hashtags for Short-form Videos with Guided Signals. - Tiezheng Yu; Hanchao Yu; Davis Liang; Yuning Mao; Shaoliang Nie; Po-Yao Huang 001; Madian Khabsa; Pascale Fung; Yi-Chia Wang (ACL (1), 2023)

RoAST: Robustifying Language Models via Adversarial Perturbation with Selective Training. - Jaehyung Kim 001; Yuning Mao; Rui Hou; Hanchao Yu; Davis Liang; Pascale Fung; Qifan Wang 001; Fuli Feng; Lifu Huang; Madian Khabsa (EMNLP (Findings), 2023)

Co-training and Co-distillation for Quality Improvement and Compression of Language Models. - Hayeon Lee; Rui Hou 007; Jongpil Kim; Davis Liang; Hongbo Zhang; Sung Ju Hwang; Alexander Min (EMNLP (Findings), 2023)

XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models. - Davis Liang; Hila Gonen; Yuning Mao; Rui Hou; Naman Goyal 001; Marjan Ghazvininejad; Luke Zettlemoyer; Madian Khabsa (EMNLP, 2023)

The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants. - Lucas Bandarkar; Davis Liang; Benjamin Muller; Mikel Artetxe; Satya Narayan Shukla; Donald Husa; Naman Goyal 001; Abhinandan Krishnan; Luke Zettlemoyer; Madian Khabsa (ACL (1), 2024)

The Curious Language Model: Strategic Test-Time Information Acquisition. - Michael Cooper; Rohan Wadhawan; John Michael Giorgi; Chenhao Tan; Davis Liang (CoRR, 2025)

From Feedback to Checklists: Grounded Evaluation of AI-Generated Clinical Notes. - Karen Zhou 001; John M. Giorgi; Pranav Mani; Peng Xu; Davis Liang; Chenhao Tan (CoRR, 2025)