14 papers
The Personalization Trap: How User Memory Alters Emotional Reasoning in LLMs
Xi Fang, Weijie Xu, Yuchong Zhang +3
When an AI assistant remembers that Sarah is a single mother working two jobs, does it interpret her stress differently than if she were a wealthy executive? As personalized AI sys…
Visual Exclusivity Attacks: Automatic Multimodal Red Teaming via Agentic Planning
Yunbei Zhang, Yingqiang Ge, Weijie Xu +3
Current multimodal red teaming treats images as wrappers for malicious payloads via typography or adversarial noise. These attacks are structurally brittle, as standard defenses ne…
Distractor Injection Attacks on Large Reasoning Models: Characterization and Defense
Zhehao Zhang, Weijie Xu, Shixian Cui +1
Recent advances in large reasoning models (LRMs) have enabled remarkable performance on complex tasks such as mathematics and coding by generating long Chain-of-Thought (CoT) trace…
SATA-BENCH: Select All That Apply Benchmark for Multiple Choice Questions
Weijie Xu, Shixian Cui, Xi Fang +3
Large language models (LLMs) are increasingly evaluated on single-answer multiple-choice tasks, yet many real-world problems require identifying all correct answers from a set of o…
Topological Structure Learning Should Be A Research Priority for LLM-Based Multi-Agent Systems
Jiaxi Yang, Mengqi Zhang, Yiqiao Jin +8
Large Language Model-based Multi-Agent Systems (MASs) have emerged as a powerful paradigm for tackling complex tasks through collaborative intelligence. However, the topology of th…
Quantifying Fairness in LLMs Beyond Tokens: A Semantic and Statistical Perspective
Weijie Xu, Yiwen Wang, Chi Xue +4
Large Language Models (LLMs) often generate responses with inherent biases, undermining their reliability in real-world applications. Existing evaluation methods often overlook bia…