1 citations · 1 across the 5 of their papers we have counts for
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Data-Constrained Language Model Pretraining: Improved Regularization and Scaling Laws
Zhiwei Xu, Shihao Wu, Hanseul Cho +2
Classical scaling laws for language model pretraining balance model size against training dataset size under a fixed compute budget, assuming abundant data and a single pass over t…
Let Me Grok for You: Accelerating Grokking via Embedding Transfer from a Weaker Model
Zhiwei Xu, Zhiyu Ni, Yixin Wang +1
''Grokking'' is a phenomenon where a neural network first memorizes training data and generalizes poorly, but then suddenly transitions to near-perfect generalization after prolong…
Benign Overfitting in Single-Head Attention
Roey Magen, Shuning Shang, Zhiwei Xu +3
The phenomenon of benign overfitting, where a trained neural network perfectly fits noisy training data but still achieves near-optimal test performance, has been extensively studi…
Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data
Zhiwei Xu, Yutong Wang, Spencer Frei +2
Neural networks trained by gradient descent (GD) have exhibited a number of surprising generalization behaviors. First, they can achieve a perfect fit to noisy training data and st…