2 citations · 4 across the 16 of their papers we have counts for
6 papers · 1 filter
Unveiling In-Context Learning: A Coordinate System to Understand Its Working Mechanism
Anhao Zhao, Fanghua Ye, Jinlan Fu +1
Large language models (LLMs) exhibit remarkable in-context learning (ICL) capabilities. However, the underlying working mechanism of ICL remains poorly understood. Recent research…
Safe Inputs but Unsafe Output: Benchmarking Cross-modality Safety Alignment of Large Vision-Language Model
Siyin Wang, Xingsong Ye, Qinyuan Cheng +5
As Artificial General Intelligence (AGI) becomes increasingly integrated into various facets of human life, ensuring the safety and ethical alignment of such systems is paramount.…
Chain of Thought Explanation for Dialogue State Tracking
Lin Xu, Ningxin Peng, Daquan Zhou +2
Dialogue state tracking (DST) aims to record user queries and goals during a conversational interaction achieved by maintaining a predefined set of slots and their corresponding va…
CET2: Modelling Topic Transitions for Coherent and Engaging Knowledge-Grounded Conversations
Lin Xu, Qixian Zhou, Jinlan Fu +1
Knowledge-grounded dialogue systems aim to generate coherent and engaging responses based on the dialogue contexts and selected external knowledge. Previous knowledge selection met…
Hint-before-Solving Prompting: Guiding LLMs to Effectively Utilize Encoded Knowledge
Jinlan Fu, Shenzhen Huangfu, Hang Yan +2
Large Language Models (LLMs) have recently showcased remarkable generalizability in various domains. Despite their extensive knowledge, LLMs still face challenges in efficiently ut…
LLM can Achieve Self-Regulation via Hyperparameter Aware Generation
Siyin Wang, Shimin Li, Tianxiang Sun +6
In the realm of Large Language Models (LLMs), users commonly employ diverse decoding strategies and adjust hyperparameters to control the generated text. However, a critical questi…