5 papers
Training Numerical Intelligence via Auto-Diagnosis and Skill Discovery
Peter Chen, Wotao Yin
AI agents are becoming increasingly capable of generating scientific code, but generating code is not the same as improving the algorithms behind it. For numerical solvers, executi…
From Search to Synthesis: Training LLMs as Zero-Shot Workflow Generators
Gan Luo, Zihan Qin, Bin Dong +1
Large language models (LLMs) excel across a wide range of tasks, yet their instance-specific solutions often lack the structural consistency needed for reliable deployment. Workflo…
Exploration vs Exploitation: Rethinking RLVR through Clipping, Entropy, and Spurious Reward
Peter Chen, Xiaopeng Li, Ziniu Li +3
This paper examines the exploration-exploitation trade-off in reinforcement learning with verifiable rewards (RLVR), a framework for improving the reasoning of Large Language Model…
ComPO: Preference Alignment via Comparison Oracles
Peter Chen, Xi Chen, Wotao Yin +1
Direct alignment methods are increasingly used for aligning large language models (LLMs) with human preferences. However, these methods suffer from the issues of verbosity and like…
Block Acceleration Without Momentum: On Optimal Stepsizes of Block Gradient Descent for Least-Squares
Liangzu Peng, Wotao Yin
Block coordinate descent is a powerful algorithmic template suitable for big data optimization. This template admits a lot of variants including block gradient descent (BGD), which…