109 citations · 182 across the 20 of their papers we have counts for
5 papers · 1 filter
Do Uncertainty Signals Help? A Systematic Study of Uncertainty-Aware Decoding with Rollback Mechanisms
Xianzong Wu, Xiaohong Li, Yuejun Guo +4
Prediction uncertainty is a widely adopted metric for quantifying model confidence, with downstream applications spanning model explanation, data selection, and prediction rollback…
KernelClaw: A Multi-Agent Framework for GPU Kernel Optimization with Dual-Memory Mechanisms
Qitong Sun, Jun Han, Tianlin Li +6
Improving GPU kernel efficiency is crucial for efficient AI systems. Recent work has explored leveraging large language models (LLMs) for GPU kernel generation and optimization. Ho…
FAIRER: Fairness as Decision Rationale Alignment
Tianlin Li, Qing Guo, Aishan Liu +3
Deep neural networks (DNNs) have made significant progress, but often suffer from fairness issues, as deep models typically show distinct accuracy differences among certain subgrou…
NPC: Neuron Path Coverage via Characterizing Decision Logic of Deep Neural Networks
Xiaofei Xie, Tianlin Li, Jian Wang +4
Deep learning has recently been widely applied to many applications across different domains, e.g., image classification and audio recognition. However, the quality of Deep Neural…
Knowledge Consistency between Neural Networks and Beyond
Ruofan Liang, Tianlin Li, Longfei Li +2
This paper aims to analyze knowledge consistency between pre-trained deep neural networks. We propose a generic definition for knowledge consistency between neural networks at diff…