4 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CL2025
EasyDistill: A Comprehensive Toolkit for Effective Knowledge Distillation of Large Language Models
Chengyu Wang, Junbing Yan, Wenrui Cai +2
In this paper, we present EasyDistill, a comprehensive toolkit designed for effective black-box and white-box knowledge distillation (KD) of large language models (LLMs). Our frame…
cs.CL2025★ 4 cited
SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines
P Team, Xinrun Du, Yifan Yao +94
Large language models (LLMs) have demonstrated remarkable proficiency in mainstream academic disciplines such as mathematics, physics, and computer science. However, human knowledg…
cs.CL2024★ 1 cited
Building a Family of Data Augmentation Models for Low-cost LLM Fine-tuning on the Cloud
Yuanhao Yue, Chengyu Wang, Jun Huang +1
Specializing LLMs in various domain-specific tasks has emerged as a critical step towards achieving high performance. However, the construction and annotation of datasets in specif…