activity
20232026
most citedHuman Cognitive Benchmarks Reveal Foundational Visual Gaps in MLLMs

2 citations · 2 across the 7 of their papers we have counts for

collaborators

20 papers

cs.LG2026

TRACE: Trajectory-Based Safety Patch Learning for LLM Post-Training Realignment

Changyue Li, Jiaming He, Youliang Yuan +4

Fine-Tuning-as-a-Service (FTaaS) platforms let users train large language models (LLMs) on customized tasks, but this pipeline could erode models' safety alignment. In practice, se…

cs.CL2026

SHAPE: Unifying Safety, Helpfulness and Pedagogy for Educational LLMs

Sihang Zhao, Kangrui Yu, Youliang Yuan +2

Large Language Models (LLMs) have been widely explored in educational scenarios. We identify a critical vulnerability in current educational LLMs, pedagogical jailbreaks, where stu…

cs.CV2025

Semantic Router: On the Feasibility of Hijacking MLLMs via a Single Adversarial Perturbation

Changyue Li, Jiaying Li, Youliang Yuan +3

Multimodal Large Language Models (MLLMs) are increasingly deployed in stateless systems, such as autonomous driving and robotics. This paper investigates a novel threat: Semantic-A…

cs.CL2025

Curing Miracle Steps in LLM Mathematical Reasoning with Rubric Rewards

Youliang Yuan, Qiuyang Mang, Jingbang Chen +7

In this paper, we observe that current models are susceptible to reward hacking, leading to a substantial overestimation of a model's reasoning ability. This is evidenced by a high…

cs.CL2025

Towards Evaluating Proactive Risk Awareness of Multimodal Language Models

Youliang Yuan, Wenxiang Jiao, Yuejin Xie +5

Human safety awareness gaps often prevent the timely recognition of everyday risks. In solving this problem, a proactive safety artificial intelligence (AI) system would work bette…

cs.CV2025

VisBias: Measuring Explicit and Implicit Social Biases in Vision Language Models

Jen-tse Huang, Jiantong Qin, Jianping Zhang +3

This research investigates both explicit and implicit social biases exhibited by Vision-Language Models (VLMs). The key distinction between these bias types lies in the level of aw…