Sitong Fang
Undergraduate Student, Yuanpei College, Peking University
I am a senior undergraduate majoring in Artificial Intelligence at Yuanpei College, Peking University, advised by Prof. Yaodong Yang. I am a member of the PKU Alignment Group and a Research Scientist at Physis AI.
My research focuses on trustworthy multimodal AI and physically grounded world models. I have introduced TruthfulVQA (ACL 2026), the first benchmark for multimodal truthfulness, and Debate with Images (preprint, 2025), a visually grounded multi-agent debate framework for detecting deception in multimodal LLMs, along with MM-DeceptionBench, the first benchmark for multimodal deception. I am also a co-first author of the AI Deception Survey, the first systematic international survey on AI deception, with Turing Award laureate Andrew Yao as corresponding author.
News
- 2026.04 One paper accepted at ACL 2026.
- 2025.11 Our survey AI Deception released, the first systematic international report on AI deception, with Turing Award laureate Andrew Yao as the corresponding author.
- 2026.09 Debate with Images released, introducing MM-DeceptionBench and a multi-agent debate framework for multimodal deception detection.
- 2025.06 Eval-Anything open-sourced at PKU-Alignment. Debate with Images released, introducing MM-DeceptionBench and a multi-agent debate framework for multimodal deception detection.
- 2025.05 Awarded Beijing Natural Science Foundation Undergraduate QiYan Research Program Grant.
Honors and Awards
- 2025 Yuanpei Young Scholar (10 annual recipients)
- 2025 Beijing Natural Science Foundation Undergraduate QiYan Research Program (Sole recipient in the cohort)
- 2025 Soong Ching Ling Future Scholarship (national undergraduate scholarship)
- 2024 Peking University Boya Scholarship
- 2024 Peking University Academic Excellence Award, Social Service Award
- 2023 Peking University Freshman Scholarship (First Prize)
- 2023 Ranked 1st in Fujian Province, National College Entrance Exam (Science)
Selected Publications
2026
2025
Experiences
Building physically grounded world foundation models with reinforcement learning.
- Core contributor to Align-Anything (4k+ ★): All-modality alignment framework
- Core contributor to Eval-Anything: All-modality safety evaluation framework
Contributed to HKGAI-V1, the Hong Kong government's first locally fine-tuned generative AI model, focusing on safety alignment for Cantonese, Mandarin, and English.
Educations
- 2023 - Present B.S. in Artificial Intelligence, Yuanpei College, Peking University