5 citations · 5 across the 1 of their papers we have counts for
4 papers
IndiVec: An Exploration of Leveraging Large Language Models for Media Bias Detection with Fine-Grained Bias Indicators
Luyang Lin, Lingzhi Wang, Xiaoyan Zhao +2
This study focuses on media bias detection, crucial in today's era of influential social media platforms shaping individual attitudes and opinions. In contrast to prior work that p…
TPE: Towards Better Compositional Reasoning over Conceptual Tools with Multi-persona Collaboration
Hongru Wang, Huimin Wang, Lingzhi Wang +6
Large language models (LLMs) have demonstrated exceptional performance in planning the use of various functional tools, such as calculators and retrievers, particularly in question…
Delta-LoRA: Fine-Tuning High-Rank Parameters with the Delta of Low-Rank Matrices
Bojia Zi, Xianbiao Qi, Lingzhi Wang +3
In this paper, we present Delta-LoRA, which is a novel parameter-efficient approach to fine-tune large language models (LLMs). In contrast to LoRA and other low-rank adaptation met…
KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment
Lingzhi Wang, Tong Chen, Wei Yuan +3
Recent legislation of the "right to be forgotten" has led to the interest in machine unlearning, where the learned models are endowed with the function to forget information about…