collaborators

10 papers

cs.CR2026

MemCatalyst: Amplifying Data Auditing on Vision-Language Models via Data Poisoning

Xukun Luan, Jinyan Liu, Yuhui Gong +4

Vision-Language models (VLMs) achieve outstanding performance largely due to the amount of training data available on the internet. At the same time, data holders (e.g., artists) u…

cs.CL2026

MicroVerse: An Instrument for Measuring Self-Authored Identity Drift in Long-Horizon Multi-Agent Language-Model Simulations

Sky Ng, Brihi Joshi, Ishan Gupta +47

Long-horizon, multi-agent language model (LM) simulations are widely proposed for studying social behavior, yet instruments to measure whether persona-conditioned agents maintain i…

cs.HC2026

PersonaEval: Persona-Based User Simulation for Evaluating Interactive Applications

Yifan Simon Liu, Qianfeng Wen, Yilan Fan +40

Real user studies are important for understanding how people interact with systems under test or already deployed. In practice, however, they are often costly, time-consuming, and…

cs.AI2026

MatrAIx: Simulating the World with 8.3 Billion Persona Agents

Xiaomin Li, Yuexing Hao, Jianheng Hou +90

Human evaluation of AI systems and digital products is costly, slow, and difficult to scale. Offline evaluations are more scalable but often abstract away human diversity and inter…

cs.CV2026

When Think-with-Image Meets Safety: What Determines Multimodal Jailbreak Robustness?

Yuan Tian, Bing Hu, Fang Wu +3

Think-with-image reasoning is emerging as a new inference paradigm for large vision-language models, but its safety implications remain poorly understood. Existing systems already…

cs.DC2026

PipeSD: An Efficient Cloud-Edge Collaborative Pipeline Inference Framework with Speculative Decoding

Yunhe Han, Yunqi Gao, Bing Hu +4

Speculative decoding can significantly accelerate LLM inference, especially given that its cloud-edge collaborative deployment offers cloud workload offloading, offline robustness,…