3 papers
cs.CL2025
Attention Basin: Why Contextual Position Matters in Large Language Models
Zihao Yi, Delong Zeng, Zhenqing Ling +6
The performance of Large Language Models (LLMs) is significantly sensitive to the contextual position of information in the input. To investigate the mechanism behind this position…
cs.CV2025
MindGYM: What Matters in Question Synthesis for Thinking-Centric Fine-Tuning?
Zhe Xu, Daoyuan Chen, Zhenqing Ling +2
Large foundation models face challenges in acquiring transferable, structured thinking abilities, especially when supervised with rigid templates or crowd-annotated instruction dat…
cs.CL2024
Intent-driven In-context Learning for Few-shot Dialogue State Tracking
Zihao Yi, Zhe Xu, Ying Shen
Dialogue state tracking (DST) plays an essential role in task-oriented dialogue systems. However, user's input may contain implicit information, posing significant challenges for D…