most citedSurvey on Knowledge Distillation for Large Language Models: Methods, Evaluation, and Application

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CL2025

A Language Anchor-Guided Method for Robust Noisy Domain Generalization

Zilin Dai, Lehong Wang, Fangzhou Lin +5

Real-world machine learning applications often struggle with two major challenges: distribution shift and label noise. Models tend to overfit by focusing on redundant and uninforma…

cs.CL2024★ 2 cited

Survey on Knowledge Distillation for Large Language Models: Methods, Evaluation, and Application

Chuanpeng Yang, Wang Lu, Yao Zhu +5

Large Language Models (LLMs) have showcased exceptional capabilities in various domains, attracting significant interest from both academia and industry. Despite their impressive p…