Yunmo Chen

/ɥín mʷòː ʈʂʰə́n/

Bloomberg LP

Senior Scientist

Bio

I am a Senior Scientist at Bloomberg. I obtained my PhD from Johns Hopkins University, where I was advised by Prof. Benjamin Van Durme. My research interests are structured prediction (e.g. semantic parsing, code generation, information extraction) and sequence modeling (e.g. machine translation, streaming sequence transduction).

Recently, I have been working on large language models (LLMs) projects including using reinforcement learning (RL) to improve model steerability and robustness, retrieval augmented generation (RAG) for long-form question answering, and model fine-tuning with preference and demonstration data. I was awarded outstanding paper for Learning to Retrieve Iteratively for In-Context Learning at EMNLP 2024 and Iterative Document-level Information Extraction via Imitation Learning at EACL 2023.

Preprints

Weiting Tan, Yunmo Chen, Tongfei Chen, Guanghui Qin, Haoran Xu, Heidi Zhang, Benjamin Van Durme, Philipp Koehn
Streaming Sequence Transduction through Dynamic Compression

In arXiv:2402.01172, 2024.

Publications

Yunmo Chen, Tongfei Chen, Harsh Jhamtani, Patrick Xia, Richard Shin, Jason Eisner, Benjamin Van Durme
Learning to Retrieve Iteratively for In-Context Learning

In Empirical Methods in Natural Language Processing (EMNLP), 2024.

Outstanding Paper Award

Liqiang Jing, Ruosen Li, Yunmo Chen, Mengzhao Jia, Xinya Du
FaithScore: Evaluating Hallucinations in Large Vision-Language Models

In Empirical Methods in Natural Language Processing (EMNLP), findings, 2024.

Lingfeng Shen, Weiting Tan, Sihao Chen, Yunmo Chen, Jingyu Zhang, Haoran Xu, Boyuan Zheng, Philipp Koehn, Daniel Khashabi
The Language Barrier: Dissecting Safety Challenges of LLMs in Multilingual Contexts

In Association for Computational Linguistics (ACL), findings, 2024.

Haoran Xu, Amr Sharaf, Yunmo Chen, Weiting Tan, Lingfeng Shen, Benjamin Van Durme, Kenton Murray, Young Jin Kim
Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation

In International Conference on Machine Learning (ICML), 2024.

Weiting Tan, Haoran Xu, Lingfeng Shen, Shuyue Stella Li, Kenton Murray, Philipp Koehn, Benjamin Van Durme, Yunmo Chen
Narrowing the Gap between Zero- and Few-shot Machine Translation by Matching Styles

In North American Chapter of the Association for Computational Linguistics (NACL), 2024.

William Gantt, Shabnam Behzad, Hannah YoungEun An, Yunmo Chen, Aaron Steven White, Benjamin Van Durme, Mahsa Yarmohammadi
MultiMUC: Multilingual Template Filling on MUC-4

In European Chapter of the Association for Computational Linguistics (EACL), 2024.

Yunmo Chen*, William Gantt*, Tongfei Chen*, Aaron Steven White, Benjamin Van Durme
A Unified View of Evaluation Metrics for Structured Prediction

In Empirical Methods in Natural Language Processing (EMNLP), 2023.

CodePackage

Haoran Xu, Weiting Tan*, Shuyue Stella Li*, Yunmo Chen*, Benjamin Van Durme, Philipp Koehn, Kenton Murray
Condensing Multilingual Knowledge with Lightweight Language-Specific Modules

In Empirical Methods in Natural Language Processing (EMNLP), 2023.

William Gantt, Reno Kriz*, Yunmo Chen*, Siddharth Vashishtha*, Aaron Steven White
On Event Individuation for Document-Level Information Extraction

In Empirical Methods in Natural Language Processing (EMNLP), findings, 2023.

Code

Kangda Wei, Dawn Lawrie, Benjamin Van Durme, Yunmo Chen, Orion Weller
When Do Decompositions Help for Machine Reading?

In Empirical Methods in Natural Language Processing (EMNLP), 2023.

Yunmo Chen, William Gantt, Weiwei Gu, Tongfei Chen, Aaron Steven White, Benjamin Van Durme
Iterative Document-level Information Extraction via Imitation Learning

In European Chapter of the Association for Computational Linguistics (EACL), 2023.

Outstanding Paper Award

PosterCode

Paul Soulos, Edward J. Hu, Kate McCurdy, Yunmo Chen, Roland Fernandez, Paul Smolensky, Jianfeng Gao
Differentiable Tree Operations Promote Compositional Generalization

In International Conference on Machine Learning (ICML), 2023.

PosterCode

Weiwei Gu*, Boyuan Zheng*, Yunmo Chen, Tongfei Chen, Benjamin Van Durme
An Empirical Study on Finding Spans

In Empirical Methods in Natural Language Processing (EMNLP), 2022.

Poster

Mahsa Yarmohammadi, Shijie Wu, Marc Marone, Haoran Xu, Seth Ebner, Guanghui Qin, Yunmo Chen, Jialiang Guo, Craig Harman, Kenton Murray, Aaron White, Mark Dredze, Benjamin Van Durme
Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction

In Empirical Methods in Natural Language Processing (EMNLP), 2021.

Code

Patrick Xia, Guanghui Qin, Siddharth Vashishtha, Yunmo Chen, Tongfei Chen, Chandler May, Craig Harman, Kyle Rawlins, Aaron Steven White, Benjamin Van Durme
LOME: Large Ontology Multilingual Extraction

In Association for Computational Linguistics (ACL), System Demo, 2021.

Code

Yunmo Chen, Sixing Lu, Fan Yang, Xiaojiang Huang, Xing Fan, Chenlei Guo
Pattern-aware Data Augmentation for Query Rewriting in Voice Assistant Systems

In DEEP-DIAL at AAAI, 2021.

Tongfei Chen, Yunmo Chen, Benjamin Van Durme
Hierarchical Entity Typing via Multi-level Learning to Rank

In Association for Computational Linguistics (ACL), 2020.

Code

Yunmo Chen, Tongfei Chen, Benjamin Van Durme
Joint Modeling of Arguments for Event Understanding

In Computational Approaches to Discourse (CODI) at EMNLP, 2020.

Code

Yunmo Chen, Tongfei Chen, Seth Ebner, Aaron Steven White, Benjamin Van Durme
Reading the Manual: Event Extraction as Definition Comprehension

In Structured Prediction for NLP (SPNLP) at EMNLP, 2020.