2 citations · 2 across the 9 of their papers we have counts for
3 papers · 1 filter
A rationale from frequency perspective for grokking in training neural network
Zhangchen Zhou, Yaoyu Zhang, Zhi-Qin John Xu
Grokking is the phenomenon where neural networks NNs initially fit the training data and later generalize to the test data during training. In this paper, we empirically provide a…
Understanding the Language Model to Solve the Symbolic Multi-Step Reasoning Problem from the Perspective of Buffer Mechanism
Zhiwei Wang, Yunji Wang, Zhongwang Zhang +7
Large language models have consistently struggled with complex reasoning tasks, such as mathematical problem-solving. Investigating the internal reasoning mechanisms of these model…
Anchor function: a type of benchmark functions for studying language models
Zhongwang Zhang, Zhiwei Wang, Junjie Yao +4
Understanding transformer-based language models is becoming increasingly crucial, particularly as they play pivotal roles in advancing towards artificial general intelligence. Howe…