1 citations · 2 across the 2 of their papers we have counts for
4 papers
When Data-Free Knowledge Distillation Meets Non-Transferable Teacher: Escaping Out-of-Distribution Trap is All You Need
Ziming Hong, Runnan Chen, Zengmao Wang +3
Data-free knowledge distillation (DFKD) transfers knowledge from a teacher to a student without access the real in-distribution (ID) data. Its common solution is to use a generator…
From Debate to Equilibrium: Belief-Driven Multi-Agent LLM Reasoning via Bayesian Nash Equilibrium
Xie Yi, Zhanke Zhou, Chentao Cao +3
Multi-agent frameworks can substantially boost the reasoning power of large language models (LLMs), but they typically incur heavy computational costs and lack convergence guarante…
Instance-dependent Early Stopping
Suqin Yuan, Runqi Lin, Lei Feng +2
In machine learning practice, early stopping has been widely used to regularize models and can save computational costs by halting the training process when the model's performance…
Enhancing Sample Selection Against Label Noise by Cutting Mislabeled Easy Examples
Suqin Yuan, Lei Feng, Bo Han +1
Sample selection is a prevalent approach in learning with noisy labels, aiming to identify confident samples for training. Although existing sample selection methods have achieved…