4 papers
Do LLMs Understand Sequential Structure? A Controlled Study of Inference and Generation
Jerry Wang, Zhengxiang Wang, Ting Yu Liu +3
Large language models (LLMs) are increasingly used as interactive agents and simulators, yet it remains unclear whether they can recover latent sequential structure beyond surface…
When Successful Knowledge Graph Edits Displace Correct Answers: Rank-Level Locality beyond Parameter Support
Yi-Cheng Lai, Jerry Wang, Hsin-Ling Hsu +3
Editing a knowledge graph embedding (KGE) model to promote a desired answer can displace correct answers from the returned list. Locality tests based only on facts that reuse the e…
Do Multimodal LLMs See Before They Read? Diagnosing Contextual Sycophancy
Yi-Cheng Lai, Hen-Hsen Huang
External text can override conflicting image evidence in multimodal large language models, a failure we call multimodal contextual sycophancy. We introduce a 998-case diagnostic th…
MANTA: Multi-Agent Network Topology Adaptation for Self-Evolving Multi-Agent Systems
Mao-xun Huang, Jerry Wang, Yi-Cheng Lai +3
Large language model-based multi-agent systems improve complex problem solving through task decomposition, agent specialization, information exchange, and intermediate validation.…