collaborators

5 papers

cs.AI2026

Agentic Game Development as a Verifiable Trajectory Data Engine for Scaling World Models

Pengfei Zhou, Hexin Wang, Zhengfeiyang Zhang +5

A common strategy for scaling world models is to train on more crawled video with more compute. We argue that this strategy is inefficient: scaling world models also requires a rec…

cs.CV2026

Can We Defend Against AI-Generated Video Attacks on Real-World Crisis Events? A Systematic Evaluation of Detectors, Generators and Social Dissemination

Shuo Liang, Yixing Ma, Pengfei Zhou +33

Recent video generators can fabricate realistic depictions of wars, disasters, public emergencies, and other real-world crises, creating substantial risks of misinformation. Existi…

cs.AI2026

Improving Generalization Robustness of Multimodal RLVR

Pengfei Zhou, Zhiwei Tang, Xiaopeng Peng +11

Reinforcement Learning with Verifiable Rewards (RLVR) makes Multimodal Large Language Models more accurate, but the gains are brittle: simply paraphrasing a question or changing th…

cs.CL2026

Unified Hallucination Fuzzing for Multimodal Large Language Models

Pengfei Zhou, Jiajun Song, Zhiwei Tang +12

Hallucination remains a persistent challenge for Multimodal Large Language Models (MLLMs), severely limiting their reliability in high-stakes applications. Existing evaluations, pr…

cs.AI2026

Agent-as-a-Router: Agentic Model Routing for Coding Tasks

Pengfei Zhou, Zhiwei Tang, Yixing Ma +8

Real-world users typically have access to multiple Large Language Models (LLMs) from different providers, and these LLMs often excel at distinct domains, yet none dominate all. Con…