2 citations · 3 across the 17 of their papers we have counts for
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Addressing Performance Saturation for LLM RL via Precise Entropy Curve Control
Bolian Li, Yifan Wang, Yi Ding +3
Reinforcement learning (RL) has enabled complex reasoning abilities in large language models (LLMs). However, most RL algorithms suffer from performance saturation, preventing cont…
Uniform-Correct Policy Optimization: Breaking RLVR's Indifference to Diversity
Anamika Lochab, Bolian Li, Ruqi Zhang
Reinforcement Learning with Verifiable Rewards (RLVR) has achieved substantial gains in single-attempt accuracy (Pass@1) on reasoning tasks, yet often suffers from reduced multi-sa…
Stacey: Promoting Stochastic Steepest Descent via Accelerated -Smooth Nonconvex Optimization
Xinyu Luo, Cedar Site Bai, Bolian Li +3
While popular optimization methods such as SGD, AdamW, and Lion depend on steepest descent updates in either or norms, there remains a critical gap in handli…
Bayesian Computation in Deep Learning
Wenlong Chen, Bolian Li, Ruqi Zhang +1
Bayesian methods have shown success in deep learning applications. For example, in predictive tasks, Bayesian neural networks leverage Bayesian reasoning of model uncertainty to im…
Making Reliable and Flexible Decisions in Long-tailed Classification
Bolian Li, Ruqi Zhang
Long-tailed classification is challenging due to its heavy imbalance in class probabilities. While existing methods often focus on overall accuracy or accuracy for tail classes, th…
Entropy-MCMC: Sampling from Flat Basins with Ease
Bolian Li, Ruqi Zhang
Bayesian deep learning counts on the quality of posterior distribution estimation. However, the posterior of deep neural networks is highly multi-modal in nature, with local modes…
Long-tailed Classification from a Bayesian-decision-theory Perspective
Bolian Li, Ruqi Zhang
Long-tailed classification poses a challenge due to its heavy imbalance in class probabilities and tail-sensitivity risks with asymmetric misprediction costs. Recent attempts have…