11 citations · 11 across the 4 of their papers we have counts for
5 papers
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…
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…
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…
Dynamic Demonstration Retrieval and Cognitive Understanding for Emotional Support Conversation
Zhe Xu, Daoyuan Chen, Jiayi Kuang +3
Emotional Support Conversation (ESC) systems are pivotal in providing empathetic interactions, aiding users through negative emotional states by understanding and addressing their…
A Survey on Recent Advances in LLM-Based Multi-turn Dialogue Systems
Zihao Yi, Jiarui Ouyang, Zhe Xu +4
This survey provides a comprehensive review of research on multi-turn dialogue systems, with a particular focus on multi-turn dialogue systems based on large language models (LLMs)…