collaborators

5 papers

cs.HC2026

Do Models See in Line with Human Vision? Probing the Correspondence Between LVLM Representations and EEG Signals

Xin Xiao, Yang Lei, Haoyang Zeng +6

Large Vision Language Models (LVLMs) exhibit strong visual understanding and reasoning abilities. However, whether their internal representations reflect human visual cognition is…

cs.SD2026

Do Models Hear Like Us? Probing the Representational Alignment of Audio LLMs and Naturalistic EEG

Haoyun Yang, Xin Xiao, Jiang Zhong +5

Audio Large Language Models (Audio LLMs) have demonstrated strong capabilities in integrating speech perception with language understanding. However, whether their internal represe…

cs.CL2026

ES-Mem: Event Segmentation-Based Memory for Long-Term Dialogue Agents

Huhai Zou, Tianhao Sun, Chuanjiang He +6

Memory is critical for dialogue agents to maintain coherence and enable continuous adaptation in long-term interactions. While existing memory mechanisms offer basic storage and re…

cs.CL2026

DiffER: Diffusion Entity-Relation Modeling for Reversal Curse in Diffusion Large Language Models

Shaokai He, Kaiwen Wei, Xinyi Zeng +5

The "reversal curse" refers to the phenomenon where large language models (LLMs) exhibit predominantly unidirectional behavior when processing logically bidirectional relationships…

cs.HC2026

Exploring Similarity between Neural and LLM Trajectories in Language Processing

Xin Xiao, Kaiwen Wei, Jiang Zhong +2

Understanding the similarity between large language models (LLMs) and human brain activity is crucial for advancing both AI and cognitive neuroscience. In this study, we provide a…