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20192026
most citedTime Matters in Regularizing Deep Networks: Weight Decay and Data Augmentation Affect Early Learning Dynamics, Matter Little Near Convergence

21 citations · 26 across the 10 of their papers we have counts for

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cs.AI2025

Re-FORC: Adaptive Reward Prediction for Efficient Chain-of-Thought Reasoning

Renos Zabounidis, Aditya Golatkar, Michael Kleinman +3

We propose Re-FORC, an adaptive reward prediction method that, given a query, enables prediction of the expected future rewards as a function of the number of future thinking token…