Bowen Zhou
Professor
Works on general AI, large language models, natural language processing, AI safety and alignment, and AI for science.
Bowen Zhou's lab at Tsinghua works on large language models, interpretability, evaluation & safety of LMs and trustworthy & safe ML. 27 papers since 2023, 18 at top venues, mostly EMNLP and ICLR. Applications close .
At a glance
- papers, 2023–2026
- 7/ year
- at T1 venues
- 67%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 5 papers2026 · T1 3 · collecting
- 4 papers2025 · T1 3
- 13 papers2024 · T1 9
- 5 papers2023 · T1 3
T1 venuesOtherVenues: EMNLP, ICLR, ACL, NAACL, NeurIPS
Research focuspaper titles that use each topic's words
- Large language models16 papers
- Interpretability, evaluation & safety of LMs2 papers
- Trustworthy & safe ML2 papers
- general0 papers
- alignment0 papers
Paper list
From the lab homepage.
20265 papers
- Cell Reports MedicineIntegrating Speech Biomarkers and Large Language Models for Adolescent Suicide Risk Detection with Mobile Application for Real-World Evaluation.” (opens in a new tab)
- Transactions on Machine Learning Research (TMLR), .Process Reinforcement Through Implicit Rewards (opens in a new tab)
- ICLR (T1)Reducing Human Priors in Scalable Formal Software Verification with RL in LLMs — A Preliminary Study on Dafny (opens in a new tab)
- ICLR (T1)The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models (opens in a new tab)
- Nature (T1)Toward the Construction of a Virtual Yeast (opens in a new tab)
20254 papers
- ICLR (T1)Advancing llm reasoning generalists with preference trees (opens in a new tab)
- ICLR (T1)OpenPRM: Building Open-domain Process-based Reward Models with Preference Trees (opens in a new tab)
- NeurIPS (T1)TTRL: Test-Time Reinforcement Learning. (opens in a new tab)
- 中国计算机学会通讯, , 21(1): 54-62.以通专融合方式构建AGI——路径与关键问题 (opens in a new tab)
202413 papers
- Communications of CCFBuilding AGI through Specialized Generalist AI: pathways and key issues. (opens in a new tab)
- ACL (T1)Cogenesis: A framework collaborating large and small language models for secure context-aware instruction following (opens in a new tab)
- CIKM (T1)Empowering private tutoring by chaining large language models (opens in a new tab)
- IEEE Signal Processing Letters. /4Enhancing adversarial transferability via information bottleneck constraints (opens in a new tab)
- NeurIPS (T1)Exploring adversarial robustness of deep state space models (opens in a new tab)
- International Journal of Artificial Intelligence and Robotics Research. /3Generative ai for complex scenarios: Language models are sequence processors (opens in a new tab)
- COLMLarge language models as biomedical hypothesis generators: a comprehensive evaluation (opens in a new tab)
- EMNLP (T1)MSI-Agent: Incorporating Multi-Scale Insight into Embodied Agents for Superior Planning and Decision-Making (opens in a new tab)
- NAACL (T1)On Large Language Models' Hallucination with Regard to Known Facts (opens in a new tab)
- EMNLP (T1)On the token distance modeling ability of higher RoPE attention dimension (opens in a new tab)
- NAACL (T1)PaD: Program-aided distillation can teach small models reasoning better than chain-of-thought fine-tuning (opens in a new tab)
- EMNLP (T1)Scalable Efficient Training of Large Language Models with Low-dimensional Projected Attention (opens in a new tab)
20235 papers
- EMNLP (T1)and Sharing Enhance Fine-tuning without Full Large Language Model (opens in a new tab)
- EMNLP (T1)Enhancing chat language models by scaling high-quality instructional conversations (opens in a new tab)
- IEEE transactions on neural networks and learning systems. /8Improving robustness of intent detection under adversarial attacks: A geometric constraint perspective (opens in a new tab)
- EMNLP (T1)Sparse low-rank adaptation of pre-trained language models (opens in a new tab)
- ACM Computing Surveys, .Trustworthy AI: From Principles to Practices (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to TsinghuaFall 2027
Computer Science PhD (international applicants)
- Round
- Main
- Opens
- GRE
- See program page
- English
- Per school catalog
- Fee
- RMB 800
Not yet confirmed for this intake.
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Data
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- The alumni list could not be found on the lab site.
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- The lab homepage
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