Author

Taiwei Shi

Observed name: Shi, Taiwei

Institutions: University of Southern California, University of Minnesota, University of Wisconsin System, University of Wisconsin–Madison, University of California San Diego

Observed institutions: University of Southern California, University of Minnesota, University of Wisconsin System, Georgia Institute of Technology, University of Wisconsin–Madison, University of California San Diego, Stanford University

OpenAlex ID: A5113985908

CoAnnotating: Uncertainty-Guided Work Allocation between Human and Large Language Models for Data Annotation

2023 · Minzhi Li, Taiwei Shi, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 47

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Safer-Instruct: Aligning Language Models with Automated Preference Data

2024 · Taiwei Shi, Kai Chen, et al. · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · 7

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Neural Story Planning

2022 · Ye, Anbang, Cui, Christopher, et al. · arXiv (Cornell University) · 5

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Safer-Instruct: Aligning Language Models with Automated Preference Data

2023 · Shi, Taiwei, Chen, Kai, et al. · arXiv (Cornell University) · 2

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WildFeedback: Aligning LLMs With In-situ User Interactions And Feedback

2026 · Taiwei Shi, Zhuoer Wang, et al. · Annual Meeting of the Association for Computational Linguistics (ACL) · 1

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CoAct-1: Computer-using Multi-Agent System with Coding Actions

2025 · Song, Linxin, Dai, Yutong, et al. · arXiv (Cornell University) · 1

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On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective

2025 · Huang, Yue, Gao, Chujie, et al. · arXiv (Cornell University) · 1

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Scheduling and energy management in a renewable-energy-driven microgrid with mobile charging robots: A structure-aware reinforcement learning approach

2026 · Taiwei Shi, Yingjun Shen, et al. · Sustainable Energy Technologies and Assessments

WildFeedback: Aligning LLMs With In-situ User Interactions And Feedback

2026 · Association for Computational Linguistics 2026, Chen, Sihao, et al. · Underline Science Inc.

Skill Reuse as Compression in Agentic RL

2026 · Xu, Zhikun, Feng, Yu, et al. · arXiv (Cornell University)

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Self-Evolving LLM Memory Extraction Across Heterogeneous Tasks

2026 · Yang, Yuqing, Liu, Tengxiao, et al. · arXiv (Cornell University)

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The Blind Spot of Agent Safety: How Benign User Instructions Expose Critical Vulnerabilities in Computer-Use Agents

2026 · Ding, Xuwei, Zhai, Skylar, et al. · arXiv (Cornell University)

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DP-RFT: Learning to Generate Synthetic Text via Differentially Private Reinforcement Fine-Tuning

2026 · Xu, Fangyuan, Chen, Sihao, et al. · arXiv (Cornell University)

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Experiential Reinforcement Learning

2026 · Shi, Taiwei, Chen, Sihao, et al. · arXiv (Cornell University)

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One Model, All Roles: Multi-Turn, Multi-Agent Self-Play Reinforcement Learning for Conversational Social Intelligence

2026 · Jiang, Bowen, Shi, Taiwei, et al. · arXiv (Cornell University)

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Video-Based Reward Modeling for Computer-Use Agents

2026 · Linxin Song, Jieyu Zhang, et al. · Lecture notes in computer science

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Works count: 16

Citation count: 64

H-index: 3

I10-index: 1