101 citations · 101 across the 6 of their papers we have counts for
6 papers
Learning Dynamics in Continual Pre-Training for Large Language Models
Xingjin Wang, Howe Tissue, Lu Wang +2
Continual Pre-Training (CPT) has become a popular and effective method to apply strong foundation models to specific downstream tasks. In this work, we explore the learning dynamic…
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…
LDM: A Large Decision Model Imitating Human Cognition with Dynamic Memory Enhancement
Xingjin Wang, Linjing Li, Daniel Zeng
With the rapid development of large language models (LLMs), it is highly demanded that LLMs can be adopted to make decisions to enable the artificial general intelligence. Most app…
Wasserstein Diversity-Enriched Regularizer for Hierarchical Reinforcement Learning
Haorui Li, Jiaqi Liang, Linjing Li +1
Hierarchical reinforcement learning composites subpolicies in different hierarchies to accomplish complex tasks.Automated subpolicies discovery, which does not depend on domain kno…
Spread-gram: A spreading-activation schema of network structural learning
Jie Bai, Linjing Li, Daniel Zeng
Network representation learning has exploded recently. However, existing studies usually reconstruct networks as sequences or matrices, which may cause information bias or sparsity…
Evolutionary dynamics of cryptocurrency transaction networks: An empirical study
Jiaqi Liang, Linjing Li, Daniel Zeng
Cryptocurrency is a well-developed blockchain technology application that is currently a heated topic throughout the world. The public availability of transaction histories offers…