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Jiecao Chen

Jiecao Chen has 3 papers in our library, in 2025–2026, most of them on Language models & pretraining, Reasoning; often with Xuesong Yao, Yufei Xu, Zhengyin Du.

3 papers in our library · 2025–2026

OpenAlex · ORCID · Wikidata · h-index 10 · 32 works · 472 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 128 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #9752

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🏢ByteDanceBeijing · China2025–2026 · 5 paperscurrent🎓Fudan UniversityShanghai · China2025 · 1 papercurrent🎓University of California, BerkeleyBerkeley · United States2025 · 1 papercurrent🎓Indiana University BloomingtonBloomington · United States2016–2019 · 10 papers🏢GoogleMountain View · United States2019–2022 · 4 papers🎓Indiana UniversityBloomington · United States2016–2017 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

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

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksInformation Systems · 1 workComputer Vision and Pattern Recognition · 1 work

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 2 worksReasoning · 1 work

 Works by year

2020s

20262 papers20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build Environments (2026 · 6 citations)
    Training LLMs to call tools with reinforcement learning is difficult for two reasons. Online APIs make training environments unstable and costly to maintain, and judging trajectories usually requires a strong LLM as evaluator, which brings bias. The authors propose FTRL, which removes both problems. An automated…
  2. Recitation over Reasoning: How Cutting-Edge Language Models Can Fail on Elementary School-Level Reasoning Problems? (2025 · 5 citations)
    The paper asks whether frontier LLMs actually reason through simple problems or mostly reproduce memorized solution templates.
  3. Beyond the Context Window: Scaling Agentic RL via End-to-end Optimized Context Compression (2026)
    Training LLM agents with reinforcement learning on long multi-turn tool-use tasks is limited by context growth.

All works

4 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

  1. WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning ↗arXiv:2103.01913 · no summary yetKrishna Srinivasan et al.2021 · 315 citations
  2. Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build EnvironmentsFindings of the Association for Computational LinguisticsJunjie Ye, Changhao Jiang, Zhengyin Du, et al.2026 · 6 citations
  3. Recitation over Reasoning: How Cutting-Edge Language Models Can Fail on Elementary School-Level Reasoning Problems?International Joint Conference on Natural Language Processing (IJCNLP)Kai Yan, Yufei Xu, Zhengyin Du, et al.2025 · 5 citations
  4. Beyond the Context Window: Scaling Agentic RL via End-to-end Optimized Context CompressionAnnual Meeting of the Association for Computational Linguistics (ACL)Miao Lu, Weiwei Sun, Weihua Du, et al.2026

 Co-authors here

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

Venues

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

 Cited by

Papers of our library cite their works 128 times (of the 149,439 papers whose bibliographies we read); 26 citing papers with a page here →.

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