Yating Wu

Research Overview

• Build computational frameworks to reveal implicit reasoning structures and trace how ideas connect in text, specifically through Questions Under Discussion.
• Develop evaluation methods to enable better and more efficient model training through structured reasoning feedback.
• Apply structured reasoning to real-world tasks such as summarization, retrieval, and elaborative text simplification.
• Advance LLM reasoning for scientific discovery as part of CosmicAI.

Education

Ph.D., (Aug. 2022 - 2026) in Computer Engineering

M.S., (Jan. 2020 - Aug. 2022) in Computer Engineering

Department of Electrical and Computer Engineering,

University of Texas at Austin.
Advisors: Prof. Jessy Li, Prof. Alex Dimakis
Group: UT NLP Group, Wireless Networking and Communications Group(WNCG)

B.Eng., (Spt. 2014 - Jul. 2019) in Computer Science and Technology

B.A., (Spt. 2014 - Jul. 2019) in Japanese

Department of Computer Science
Dalian University of Technology.

Undergraduate Exchange Student, (Spt. 2017 - Aug. 2018) in Computer Science

Department of Information & Communication Engineering,
The University of Tokyo.
Advisor: Prof. Toshihiko Yamasaki
Group: Aizawa-Yamasaki Laboratory (now Aizawa-Yamakata-Matsui Laboratory)

Preprints

• Multimodal QUD: Inquisitive Questions from Scientific Figures
  Yating Wu, William Rudman, Venkata S Govindarajan, Alexandros G. Dimakis and Junyi Jessy Li
  Preprint, 2026.

• ContextWeaver: Selective and Dependency-Structured Memory Construction for LLM Agents
  Yating Wu, Yuhao Zhang, Sayan Ghosh, Sourya Basu, Anoop Deoras, Jun Huan and Gaurav Gupta
  Preprint, 2026.

Selected Publications

(^†Indicates equal contribution)

• QUDsim: Quantifying Discourse Similarities in LLM-Generated Text [code and data]
  Ramya Namuduri, Yating Wu, Asher Zheng, Manya Wadhwa, Greg Durrett and Junyi Jessy Li.
  Conference on Language Modeling (COLM), 2025.

• Which questions should I answer? Salience Prediction of Inquisitive Questions [code and data]
  Yating Wu^†, Ritika Mangla^†, Alexandros G. Dimakis, Greg Durrett and Junyi Jessy Li
  Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024. (Oral)
  Outstanding Paper Award 🏅

• QUDeval: The Evaluation of Questions Under Discussion Discourse Parsing [code and data]
  Yating Wu, Ritika Mangla, Greg Durrett and Junyi Jessy Li
  Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023. (Oral)

• Elaborative Simplification as Implicit Questions Under Discussion [code and data]
  Yating Wu^†, William Sheffield^†, Kyle Mahowald and Junyi Jessy Li
  Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.

• Discourse Analysis via Questions and Answers: Parsing Dependency Structures of Questions Under Discussion [code]
  Wei-Jen Ko, Yating Wu, Cutter Dalton, Dananjay Srinivas, Greg Durrett and Junyi Jessy Li
  Findings of the Association for Computational Linguistics (ACL), 2023.

Workshops

(^†Indicates equal contribution)

• Modeling Bilingual Disfluencies with Large Language Models
  Negin Raoof^†, Yating Wu^†, Carlos Bonilla^†, Junyi Jessy Li, Stephanie M Grasso, Alexandros G. Dimakis and Zoi Gkalitsiou
  ICML Workshop on LLMs and Cognition, 2024.

Experience

Working Experience

• AWS AI Labs, Summer 2025
  Applied Scientist Intern. I worked on long-context memory support for LLM coding agents.
  

• Amazon Alexa AGI, Summer 2024
  Applied Scientist Intern. I worked on research problems focused on enhancing the planning and tool-using capabilities of LLM agents.
  

• Amazon Prime Video, Summer 2023
  Software Develop Engineer Intern. I implemented an in-game notification system.
  

• Amazon Prime Video, Summer 2021
  Software Develop Engineer Intern. I implemented a Java-based ranking system for live events. The project got launched in prime video offical site.

Teaching Experience

• CS391L: Machine Learning (Head TA). Summer 2022 - Fall 2025.
• CS391L: Machine Learning (TA). Fall 2021 - Summer 2022
• EE422C: Software Design & Implementation II (TA). Summer 2020 - Spring 2021

Services

• Workflow Chair, EMNLP 2026
• Reviewer: ACL ARR 2024-2025, ACL 2024-2025, EMNLP 2024, COLM 2024-2025, ICML 2025 XAI4Science, AAAI 2025 MARW, NeurIPS 2024 Behavioral ML, ICML 2024 DMLR, ICML 2024 LLMs and Cognition

Awards

• MIT EECS Rising Stars 2025
• Outstanding Paper Award in EMNLP 2024
• VMware Codehouse Palo Alto 1st place, Jul. 2021
• Outstanding graduates, Jun. 2019
• Outstanding graduates, Jun. 2014

Links

Department of Electrical and Computer Engineering

The University of Texas at Austin

The University of Tokyo

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