Zichen Liu
Zichen Liu has 3 papers in our library, in 2025–2026, most of them on Reasoning; often with Chao Du, Hang Yan, Jinjie Ni.
OpenAlex · ORCID · h-index 12 · 44 works · 430 citations OpenAlex, 2026-10-14
📄 3 works in our library · 🔗 Cited 281 times in our library · ⭐ Paper Stars ranking: #5026
Affiliations
🎓National University of SingaporeSingapore ·
Singapore2021–2026 · 5 papers🎓Beijing Technology and Business UniversityBeijing ·
China2024–2026 · 4 papers🎓Hong Kong University of Science and TechnologyHong Kong ·
China2025 · 4 papers🎓Peking UniversityBeijing ·
China2024–2025 · 4 papers🎓Shihezi UniversityShihezi ·
China2023 · 4 papers🎓Southwest Jiaotong UniversityChengdu ·
China2022–2023 · 3 papers🤝Xinjiang Production and Construction CorpsÜrümqi ·
China2023 · 3 papers🎓Northwestern Polytechnical UniversityXi'an ·
China2024–2025 · 2 papers🏛️Chinese Academy of SciencesBeijing ·
China2019–2024 · 2 papers🎓Nankai UniversityTianjin ·
China2021–2022 · 2 papers
Fields, topics and concepts
📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 3 worksLanguage and Linguistics · 3 worksArts and Humanities · 3 worksComputer Science · 3 worksMathematics · 1 workComputer Vision and Pattern Recognition · 1 work
🧭 Topics 1Research subjects and languages the work is about.Reasoning · 1 work
Works by year
2020s
Papers
- Understanding R1-Zero-Like Training: A Critical Perspective (2025 · 286 citations)
DeepSeek-R1-Zero showed that reinforcement learning applied directly to a base LLM, with no SFT stage, can strengthen reasoning. - SynthRL: Scaling Visual Reasoning with Verifiable Data Synthesis (2026 · 3 citations)
SynthRL tackles a data bottleneck in reinforcement learning with verifiable rewards (RLVR) for vision-language models. Curated question–answer pairs are costly, and data selection alone cannot go beyond the pool that already exists. The authors instead generate new training items. Their pipeline has three steps: - Breaking the Impasse: Dual-Scale Evolutionary Policy Training for Social Language Agents (2026)
The paper looks at what goes wrong when self-play reinforcement learning with verifiable rewards (RLVR) moves from closed tasks like math or code to open-ended social language games.
Co-authors here
- Chao Du
- Hang Yan
- Jinjie Ni
- Lu Wang
- Min Lin
- Minzheng Wang
- Nan Xu
- Run Luo
- Tianyu Pang
- Wee Sun Lee
- Wenji Mao
- Wenjun Li
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2026
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
Cited by
Updated
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