5 papers · 1 filter
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…
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…
Natural Language Understanding and Inference with MLLM in Visual Question Answering: A Survey
Jiayi Kuang, Jingyou Xie, Haohao Luo +6
Visual Question Answering (VQA) is a challenge task that combines natural language processing and computer vision techniques and gradually becomes a benchmark test task in multimod…
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)…