🧑‍🔬 Yisi Sang

🏛️ Affiliations

🎓Syracuse UniversitySyracuse · United States2017–2026 · 23 paperscurrent🏢AmazonSeattle · United States2026 · 5 paperscurrent🎓Northeastern UniversityBoston · United States2024–2026 · 2 paperscurrent🏢AppleCupertino · United States2023 · 2 papers🎓University of MichiganAnn Arbor · United States2023 · 2 papers🎓Hong Kong University of Science and TechnologyHong Kong · China2022 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 more institutions on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Fantastic Questions and Where to Find Them: FairytaleQA – An Authentic Dataset for Narrative Comprehension (2022 · 137 citations)
   FairytaleQA is a question-answering dataset for narrative comprehension aimed at the reading level of kindergarten to eighth-grade children.
2. Can LLM Agents Simulate Multi-Turn Human Behavior? Evidence from Real Online Customer Behavior Data (2026 · 2 citations)
   Studies of LLM agents that imitate people have mostly asked whether their behavior looks believable to human judges.
3. Trajectory2Task: Training Robust Tool-Calling Agents with Synthesized Yet Verifiable Data for Complex User Intents (2026 · 2 citations)
   Tool-calling agents used in customer service often meet users whose requests lack key details, shift during the conversation, or break system policy.
4. LLMs for Now, Fine-Tuning for Later: An Ensemble Approach to Data Drift in Domain-Specific Tasks (2026)
   Real-world domain-specific deployments, such as clinical or legal work, face two problems. Expert labels are scarce, and the incoming data keeps changing over time (data drift). Active Learning (AL) can steadily improve a small model with expert labels, but each drift returns it to a weak cold-start state. LLMs work…

All works

5 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

1. Fantastic Questions and Where to Find Them: FairytaleQA – An Authentic Dataset for Narrative ComprehensionYing Xu, Dakuo Wang, Mo Yu, et al.Mova's core list · 137 citations
2. TVShowGuess: Character Comprehension in Stories as Speaker Guessing ↗Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yetYisi Sang et al.2022 · 37 citations
3. Can LLM Agents Simulate Multi-Turn Human Behavior? Evidence from Real Online Customer Behavior DataAnnual Meeting of the Association for Computational Linguistics (ACL)Yuxuan Lu, Jing Huang, Yan Han, et al.2026 · 2 citations
4. Trajectory2Task: Training Robust Tool-Calling Agents with Synthesized Yet Verifiable Data for Complex User IntentsAnnual Meeting of the Association for Computational Linguistics (ACL)Ziyi Wang, Yuxuan Lu, Yimeng Zhang, et al.2026 · 2 citations
5. LLMs for Now, Fine-Tuning for Later: An Ensemble Approach to Data Drift in Domain-Specific TasksAnnual Meeting of the Association for Computational Linguistics (ACL)Yuxuan Lu, Bingsheng Yao, Shao Zhang, et al.2026

🤝 Co-authors here

12 of 26 co-authors with a page, the most papers together first.

• Bingsheng Yao ×3
• Dakuo Wang ×3
• Yuxuan Lu ×3
• Jing Huang ×2
• Toby Jia-Jun Li ×2
• Chen Luo
• Diyi Yang
• Hanqing Lu
• Jiri Gesi
• Mo Yu
• Nanyun Peng
• Pei Chen

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Annual Meeting of the Association for Computational Linguistics (ACL) ×4: ACL 2026 ×3, ACL 2022
• Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

🔗 Cited by

Papers of our library cite their works 101 times (of the 149,439 papers whose bibliographies we read); 19 citing papers with a page here →.

Updated 1 November 2026

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