🧑‍🔬 Xingyu Chen

🏛️ Affiliations

🏢TencentShenzhen · China2025–2026 · 6 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

🧭 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. Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs (2024 · 192 citations)
   Reasoning models in the o1 family get better accuracy by writing very long chains of thought. This paper argues that much of that extra test-time compute is wasted. The authors call the waste "overthinking": after a model already has the right answer to a trivial question, it keeps producing new solution attempts.…
2. Alignment for Efficient Tool Calling of Large Language Models (2025 · 13 citations)
   LLMs equipped with tools often misjudge when a tool is worth calling. They may call a calculator, search engine or stronger model for questions they could answer alone (over-tool-reliance), or they may skip a tool when they actually need it (overconfidence). Both errors waste time and money or lower accuracy. The…
3. Sentient Agent as a Judge: Evaluating Higher-Order Social Cognition in Large Language Models (2026 · 6 citations)
   Standard LLM leaderboards reward textual skill and helpfulness, but they rarely check whether a model actually reads people well.
4. Too Good to be Bad: On the Failure of LLMs to Role-Play Villains (2026 · 3 citations)
   LLMs are increasingly used for interactive fiction, games and co-written stories, yet nobody had systematically checked whether they can convincingly play antagonists.
5. BatonVoice: An Operationalist Framework for Enhancing Controllable Speech Synthesis with Linguistic Intelligence from LLMs (2026)
   Current LLM-based text-to-speech systems mostly use the LLM as a backbone for generating speech tokens. Controllable synthesis then depends on costly, inconsistent human annotation of speech with style labels, and the model's instruction-following ability goes largely unused. Inspired by operationalism, the authors…
6. Social Welfare Function Leaderboard: On the Emergence of LLM Agents as the Welfare Dictator (2026)
   LLMs are increasingly used in consequential settings, but little is known about the values they apply when distributing scarce resources.

🤝 Co-authors here

12 of 31 co-authors with a page, the most papers together first.

• Fanghua Ye ×4
• Ruotian Ma ×4
• Qingxuan Jiang ×3
• Qu Yang ×3
• Yue Wang ×3
• Zhaopeng Tu ×3
• Mengru Wang ×2
• Zhengliang Shi ×2
• Bang Zhang
• Dian Yu
• Jen-tse Huang
• Jiahao Xu

Venues

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

• Findings of the Association for Computational Linguistics ×3: Findings of the Association for Computational Linguistics 2026 ×3
• Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2026
• Conference on Empirical Methods in Natural Language Processing (EMNLP): EMNLP 2025

🔗 Cited by

Papers of our library cite their works 205 times (of the 149,439 papers whose bibliographies we read); 62 citing papers with a page here →.

Updated 1 November 2026

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