1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.AI2025★ 1 cited
TrustJudge: Inconsistencies of LLM-as-a-Judge and How to Alleviate Them
Yidong Wang, Yunze Song, Tingyuan Zhu +11
The adoption of Large Language Models (LLMs) as automated evaluators (LLM-as-a-judge) has revealed critical inconsistencies in current evaluation frameworks. We identify two fundam…
cs.LG2025
Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks
Miaomiao Li, Hao Chen, Yang Wang +5
Generating synthetic datasets via large language models (LLMs) has emerged as a promising approach to improve LLM performance. However, LLMs inherently reflect biases in their trai…
cs.CL2024
Learning from "Silly" Questions Improves Large Language Models, But Only Slightly
Tingyuan Zhu, Shudong Liu, Yidong Wang +4
Constructing high-quality Supervised Fine-Tuning (SFT) datasets is critical for the training of large language models (LLMs). Recent studies have shown that using data from a speci…