3 citations · 3 across the 8 of their papers we have counts for
8 papers
InstanceV: Instance-Level Video Generation
Yuheng Chen, Teng Hu, Jiangning Zhang +3
Recent advances in text-to-video diffusion models have enabled the generation of high-quality videos conditioned on textual descriptions. However, most existing text-to-video model…
The Knowledge Microscope: Features as Better Analytical Lenses than Neurons
Yuheng Chen, Pengfei Cao, Kang Liu +1
Previous studies primarily utilize MLP neurons as units of analysis for understanding the mechanisms of factual knowledge in Language Models (LMs); however, neurons suffer from pol…
One Mind, Many Tongues: A Deep Dive into Language-Agnostic Knowledge Neurons in Large Language Models
Pengfei Cao, Yuheng Chen, Zhuoran Jin +3
Large language models (LLMs) have learned vast amounts of factual knowledge through self-supervised pre-training on large-scale corpora. Meanwhile, LLMs have also demonstrated exce…
Unveiling Factual Recall Behaviors of Large Language Models through Knowledge Neurons
Yifei Wang, Yuheng Chen, Wanting Wen +3
In this paper, we investigate whether Large Language Models (LLMs) actively recall or retrieve their internal repositories of factual knowledge when faced with reasoning tasks. Thr…
MEMLA: Enhancing Multilingual Knowledge Editing with Neuron-Masked Low-Rank Adaptation
Jiakuan Xie, Pengfei Cao, Yuheng Chen +3
Knowledge editing aims to adjust the knowledge within large language models (LLMs) to prevent their responses from becoming obsolete or inaccurate. However, existing works on knowl…
Knowledge Localization: Mission Not Accomplished? Enter Query Localization!
Yuheng Chen, Pengfei Cao, Yubo Chen +2
Large language models (LLMs) store extensive factual knowledge, but the mechanisms behind how they store and express this knowledge remain unclear. The Knowledge Neuron (KN) thesis…
Cracking Factual Knowledge: A Comprehensive Analysis of Degenerate Knowledge Neurons in Large Language Models
Yuheng Chen, Pengfei Cao, Yubo Chen +4
Large language models (LLMs) store extensive factual knowledge, but the underlying mechanisms remain unclear. Previous research suggests that factual knowledge is stored within mul…
TRANSOM: An Efficient Fault-Tolerant System for Training LLMs
Baodong Wu, Lei Xia, Qingping Li +6
Large language models (LLMs) with hundreds of billions or trillions of parameters, represented by chatGPT, have achieved profound impact on various fields. However, training LLMs w…