Bio
I am a Senior Scientist at Bloomberg. At Bloomberg, I have been building an interactive code agent to help analysts retrieve and analyze the various data provided by Bloomberg. This involves implementing various training procedures to improve large language models (LLMs) on capabilities such as tool calling, and training hybrid retrieval models to improve contextual accuracy in code generation.
Previously, I obtained my PhD from Johns Hopkins University, where I was advised by Prof. Benjamin Van Durme. I worked on large language model (LLM) projects including using reinforcement learning (RL) to better orchestrate between LLMs and retrieval systems for code generation [paper], faithfullness evaluation [paper], and preference alignment algorithms [paper, paper]. My research also explored sequence modeling [paper], particularly in the context of streaming, and developed evaluation metrics for code and other structures [paper].
I was awarded outstanding paper awards for Learning to Retrieve Iteratively for In-Context Learning at EMNLP 2024 and Iterative Document-level Information Extraction via Imitation Learning at EACL 2023.
Publications
Weiting Tan,
Yunmo Chen,
Tongfei Chen,
Guanghui Qin,
Haoran Xu,
Heidi Zhang,
Benjamin Van Durme,
Philipp Koehn
Streaming Sequence Transduction through Dynamic Compression
Streaming Sequence Transduction through Dynamic Compression
In International Conference on Spoken Language Translation (IWSLT),
2025.
Yunmo Chen,
Tongfei Chen,
Harsh Jhamtani,
Patrick Xia,
Richard Shin,
Jason Eisner,
Benjamin Van Durme
Learning to Retrieve Iteratively for In-Context Learning
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
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
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
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
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
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
A Unified View of Evaluation Metrics for Structured Prediction
In Empirical Methods in Natural Language Processing (EMNLP),
2023.
Haoran Xu,
Weiting Tan*,
Shuyue Stella Li*,
Yunmo Chen*,
Benjamin Van Durme,
Philipp Koehn,
Kenton Murray
Condensing Multilingual Knowledge with Lightweight Language-Specific Modules
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
On Event Individuation for Document-Level Information Extraction
In Empirical Methods in Natural Language Processing (EMNLP), findings,
2023.
Kangda Wei,
Dawn Lawrie,
Benjamin Van Durme,
Yunmo Chen,
Orion Weller
When Do Decompositions Help for Machine Reading?
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
Iterative Document-level Information Extraction via Imitation Learning
In European Chapter of the Association for Computational Linguistics (EACL),
2023.
Outstanding Paper Award
Paul Soulos,
Edward J. Hu,
Kate McCurdy,
Yunmo Chen,
Roland Fernandez,
Paul Smolensky,
Jianfeng Gao
Differentiable Tree Operations Promote Compositional Generalization
Differentiable Tree Operations Promote Compositional Generalization
In International Conference on Machine Learning (ICML),
2023.
Weiwei Gu*,
Boyuan Zheng*,
Yunmo Chen,
Tongfei Chen,
Benjamin Van Durme
An Empirical Study on Finding Spans
An Empirical Study on Finding Spans
In Empirical Methods in Natural Language Processing (EMNLP),
2022.
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
Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction
In Empirical Methods in Natural Language Processing (EMNLP),
2021.
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
LOME: Large Ontology Multilingual Extraction
In Association for Computational Linguistics (ACL), System Demo,
2021.
Yunmo Chen,
Sixing Lu,
Fan Yang,
Xiaojiang Huang,
Xing Fan,
Chenlei Guo
Pattern-aware Data Augmentation for Query Rewriting in Voice Assistant Systems
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
Hierarchical Entity Typing via Multi-level Learning to Rank
In Association for Computational Linguistics (ACL),
2020.
Yunmo Chen,
Tongfei Chen,
Benjamin Van Durme
Joint Modeling of Arguments for Event Understanding
Joint Modeling of Arguments for Event Understanding
In Computational Approaches to Discourse (CODI) at EMNLP,
2020.
Yunmo Chen,
Tongfei Chen,
Seth Ebner,
Aaron Steven White,
Benjamin Van Durme
Reading the Manual: Event Extraction as Definition Comprehension
Reading the Manual: Event Extraction as Definition Comprehension
In Structured Prediction for NLP (SPNLP) at EMNLP,
2020.