activity
20242026
collaborators

10 papers

cs.CL2026

Representational Similarity and Model Behavior in Multi-Agent Interaction

Yujin Potter, Seun Eisape, Shiyang Lai +6

Researchers have shown that neural similarity among humans predicts social closeness and cooperative success, whereas innovation often emerges from interactions among dissimilar in…

cs.CL2026

Probing Multimodal Large Language Models on Cognitive Biases in Chinese Short-Video Misinformation

Jen-tse Huang, Chang Chen, Shiyang Lai +3

Short-video platforms have become major channels for misinformation, where deceptive claims frequently leverage visual experiments and social cues. While Multimodal Large Language…

cs.MA2026

Multi-LLM Systems Exhibit Robust Semantic Collapse

Weiyi Kong, Shiyang Lai, Jinghua Piao +1

Whether machines can originate novel content has been debated for nearly two centuries, from Lovelace's assertion that no engine can "originate anything" to Turing's question of wh…

cs.AI2026

Signal in the Noise: Polysemantic Interference Transfers and Predicts Cross-Model Influence

Bofan Gong, Shiyang Lai, James Evans +1

Polysemanticity is pervasive in language models and remains a major challenge for interpretation and model behavioral control. Leveraging sparse autoencoders (SAEs), we map the pol…

cs.CL2026

Reasoning Models Generate Societies of Thought

Junsol Kim, Shiyang Lai, Nino Scherrer +2

Large language models have achieved remarkable capabilities across domains, yet mechanisms underlying sophisticated reasoning remain elusive. Recent reasoning models outperform com…

cs.CL2026

Can Editing LLMs Inject Harm?

Canyu Chen, Baixiang Huang, Zekun Li +12

Large Language Models (LLMs) have emerged as a new information channel. Meanwhile, one critical but under-explored question is: Is it possible to bypass the safety alignment and in…