Variational Sequential Labelers for Semi-Supervised Learning. - Mingda Chen; Qingming Tang; Karen Livescu; Kevin Gimpel (EMNLP, 2018)

Smaller Text Classifiers with Discriminative Cluster Embeddings. - Mingda Chen; Kevin Gimpel (NAACL-HLT (2), 2018)

Controllable Paraphrase Generation with a Syntactic Exemplar. - Mingda Chen; Qingming Tang; Sam Wiseman; Kevin Gimpel (ACL (1), 2019)

EntEval: A Holistic Evaluation Benchmark for Entity Representations. - Mingda Chen; Zewei Chu; Yang Chen; Karl Stratos; Kevin Gimpel (EMNLP/IJCNLP (1), 2019)

Evaluation Benchmarks and Learning Criteria for Discourse-Aware Sentence Representations. - Mingda Chen; Zewei Chu; Kevin Gimpel (EMNLP/IJCNLP (1), 2019)

A Multi-Task Approach for Disentangling Syntax and Semantics in Sentence Representations. - Mingda Chen; Qingming Tang; Sam Wiseman; Kevin Gimpel (NAACL-HLT (1), 2019)

Evaluation Benchmarks and Learning Criteriafor Discourse-Aware Sentence Representations. - Mingda Chen; Zewei Chu; Kevin Gimpel (CoRR, 2019)

How to Ask Better Questions? A Large-Scale Multi-Domain Dataset for Rewriting Ill-Formed Questions. - Zewei Chu; Mingda Chen; Jing Chen; Miaosen Wang; Kevin Gimpel; Manaal Faruqui; Xiance Si (AAAI, 2020)

Mining Knowledge for Natural Language Inference from Wikipedia Categories. - Mingda Chen; Zewei Chu; Karl Stratos; Kevin Gimpel (EMNLP (Findings), 2020)

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations. - Zhenzhong Lan; Mingda Chen; Sebastian Goodman; Kevin Gimpel; Piyush Sharma; Radu Soricut (ICLR, 2020)

Learning Probabilistic Sentence Representations from Paraphrases. - Mingda Chen; Kevin Gimpel (RepL4NLP@ACL, 2020)

Controllable Paraphrasing and Translation with a Syntactic Exemplar. - Mingda Chen; Sam Wiseman; Kevin Gimpel (CoRR, 2020)

Generating Wikipedia Article Sections from Diverse Data Sources. - Mingda Chen; Sam Wiseman; Kevin Gimpel (CoRR, 2020)

WikiTableT: A Large-Scale Data-to-Text Dataset for Generating Wikipedia Article Sections. - Mingda Chen; Sam Wiseman; Kevin Gimpel (ACL/IJCNLP (Findings), 2021)

TVRecap: A Dataset for Generating Stories with Character Descriptions. - Mingda Chen; Kevin Gimpel (CoRR, 2021)

SummScreen: A Dataset for Abstractive Screenplay Summarization. - Mingda Chen; Zewei Chu; Sam Wiseman; Kevin Gimpel (ACL (1), 2022)

Improving In-Context Few-Shot Learning via Self-Supervised Training. - Mingda Chen; Jingfei Du; Ramakanth Pasunuru; Todor Mihaylov; Srini Iyer 001; Veselin Stoyanov; Zornitsa Kozareva (NAACL-HLT, 2022)

Leveraging Natural Supervision for Language Representation Learning and Generation. - Mingda Chen (CoRR, 2022)

BLASER: A Text-Free Speech-to-Speech Translation Evaluation Metric. - Mingda Chen; Paul-Ambroise Duquenne; Pierre Andrews; Justine Kao; Alexandre Mourachko; Holger Schwenk; Marta R. Costa-jussà (ACL (1), 2023)

xSIM++: An Improved Proxy to Bitext Mining Performance for Low-Resource Languages. - Mingda Chen; Kevin Heffernan; Onur Çelebi; Alexandre Mourachko; Holger Schwenk (ACL (2), 2023)

Findings of the IWSLT 2023 Evaluation Campaign. - Sweta Agrawal; Antonios Anastasopoulos; Luisa Bentivogli; Ondrej Bojar; Claudia Borg; Marine Carpuat; Roldano Cattoni; Mauro Cettolo; Mingda Chen; William Chen; Khalid Choukri; Alexandra Chronopoulou; et al. (IWSLT@ACL, 2023)

Efficient Open Domain Multi-Hop Question Answering with Few-Shot Data Synthesis. - Mingda Chen; Xilun Chen 002; Wen-tau Yih (CoRR, 2023)

A contradiction solving method for complex product conceptual design based on deep learning and technological evolution patterns. - Jiangmin Mao; Yingdan Zhu; Mingda Chen; Gang Chen; Chun Yan; Dong Liu (Adv. Eng. Informatics, 2023)

Few-Shot Data Synthesis for Open Domain Multi-Hop Question Answering. - Mingda Chen; Xilun Chen 002; Wen-tau Yih (EACL (1), 2024)

RA-DIT: Retrieval-Augmented Dual Instruction Tuning. - Xi Victoria Lin; Xilun Chen 002; Mingda Chen; Weijia Shi; Maria Lomeli; Richard James 001; Pedro Rodriguez 001; Jacob Kahn; Gergely Szilvasy; Mike Lewis; Luke Zettlemoyer; Wen-tau Yih (ICLR, 2024)

An Exploratory Study on Using Large Language Models for Mutation Testing. - Bo Wang 050; Mingda Chen; Youfang Lin; Mike Papadakis; Jie M. Zhang (CoRR, 2024)

Characterizing and Efficiently Accelerating Multimodal Generation Model Inference. - Yejin Lee 010; Anna Y. Sun; Basil Hosmer; Bilge Acun; Can Balioglu; Changhan Wang; Charles David Hernandez; Christian Puhrsch; Daniel Haziza; Driss Guessous; Francisco Massa; Jacob Kahn; et al. (CoRR, 2024)

Improving Factuality with Explicit Working Memory. - Mingda Chen; Yang Li; Karthik Padthe; Rulin Shao; Alicia Sun; Luke Zettlemoyer; Gargi Gosh; Wen-tau Yih (CoRR, 2024)

Improving Factuality with Explicit Working Memory. - Mingda Chen; Yang Li; Karthik Padthe; Rulin Shao; Alicia Yi Sun; Luke Zettlemoyer; Gargi Ghosh; Wen-tau Yih (ACL (1), 2025)

A triple-phase boost transformer for industrial equipment fault prediction. - Ruiyun Yu; Mingda Chen; Bin Liu (Neurocomputing, 2025)

A Systematic Exploration of Mutation-Based Fault Localization Formulae. - Bo Wang 050; Jinkang Wei; Mingda Chen; Chong Chen; Youfang Lin; Jie M. Zhang (Softw. Test. Verification Reliab., 2025)

ImpRAG: Retrieval-Augmented Generation with Implicit Queries. - Wenzheng Zhang; Xi Victoria Lin; Karl Stratos; Wen-tau Yih; Mingda Chen (CoRR, 2025)

FACTORY: A Challenging Human-Verified Prompt Set for Long-Form Factuality. - Mingda Chen; Yang Li; Xilun Chen 002; Adina Williams; Gargi Ghosh; Scott Yih (CoRR, 2025)

A Survey on Diffusion Language Models. - Tianyi Li; Mingda Chen; Bowei Guo; Zhiqiang Shen (CoRR, 2025)