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Junjielong Xu Profile
Junjielong Xu

@SiyuexiH

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25
Following
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17

Ph.D. student in Computer Science, The Chinese University of Hong Kong, Shenzhen.

Shenzhen
Joined February 2020
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@chao_peng_
Chao Peng
4 days
Excited to share our latest work on dynamic turn control for LLM-based Agents πŸš€ This is the first systematic study that significantly reduces Coding Agent cost with minimal impact on performance, and even improves solve rates in certain scenarios. Our method is intentionally
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@chao_peng_
Chao Peng
1 month
πŸŽ‰ Thrilled to share our new papers from @trae Research at @NeurIPSConf, @ICSEconf, and @ASE_conf β€” exploring how AI coding agents evolve from capable assistants to autonomous developers, spanning execution, evaluation, and model training. [NeurIPS Spotlight] Repo2Run β€” first
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@tuzhaopeng
Zhaopeng Tu
6 months
Trust your AI, but can it trust itself? πŸ€” Introducing an online reinforcement learning framework, RISE (Reinforcing Reasoning with Self-Verification), enabling LLMs to simultaneously level-up BOTH their problem-solving AND self-checking skills! 🧐 Problems tackled: βœ…
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@JentseHuang
J Huang
7 months
Recently we have four papers accepted to #ACL2025 and two papers accepted to #ICML2025! It is with great pleasure and excitement that all my papers during PhD study have been accepted! And I finally got first-author papers in all three ML conferences (NeurIPS, ICLR, and ICML)!
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@mboehme_
Marcel BΓΆhmeπŸ‘¨β€πŸ”¬
7 months
Our paper "Top Score on the Wrong Exam" paper will be presented at #ISSTA25 🐣 in Trondheim! πŸ“ https://t.co/m7FrZ36ach πŸ§‘β€πŸ’» https://t.co/VoItZD0KVy // @niklas2484 @fuzzjing.
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@PinjiaHE
Pinjia He
8 months
πŸ“’ Can LLMs locate software service failures? πŸ€” My student @SiyuexiH's #ICLR2025 paper introduces OpenRCA, the first benchmark dataset for evaluating LLMs' root cause analysis capabilities in software systems. LLMs/Agents need to analyze system telemetry data to infer results
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@PinjiaHE
Pinjia He
9 months
Truly humbled and honored to receive the IEEE CS TCSE Rising Star Award. Thanks a lot for the help along the way from my supervisors, referees, students, and co-authors. Will continue to focus on impactful projects about AI4SE and SE4AI. 🎯 https://t.co/cUX83bzcoQ
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@PinjiaHE
Pinjia He
10 months
πŸš€Can LLMs repair programs without known buggy hunks?πŸ€” πŸ’‘ My student @SiyuexiH's #ICSE2025 paper reveals that current infilling approaches constrain LLMs' repair potential. By simply aligning the task objective from fixing buggy hunks to rewriting the entire program with tests,
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