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20212025
most citedTrustJudge: Inconsistencies of LLM-as-a-Judge and How to Alleviate Them

1 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2025

Deep Literature Survey Automation with an Iterative Workflow

Hongbo Zhang, Han Cui, Yidong Wang +6

Automatic literature survey generation has attracted increasing attention, yet most existing systems follow a one-shot paradigm, where a large set of papers is retrieved at once an…

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.CL2023★ 1 cited

Dynamics of Instruction Fine-Tuning for Chinese Large Language Models

Chiyu Song, Zhanchao Zhou, Jianhao Yan +3

Instruction tuning is a burgeoning method to elicit the general intelligence of Large Language Models (LLMs). While numerous studies have examined the impact of factors such as dat…

cs.CL2023★ 1 cited

Understanding In-Context Learning from Repetitions

Jianhao Yan, Jin Xu, Chiyu Song +3

This paper explores the elusive mechanism underpinning in-context learning in Large Language Models (LLMs). Our work provides a novel perspective by examining in-context learning v…

cs.CL2021

Uni-Encoder: A Fast and Accurate Response Selection Paradigm for Generation-Based Dialogue Systems

Chiyu Song, Hongliang He, Haofei Yu +3

Sample-and-rank is a key decoding strategy for modern generation-based dialogue systems. It helps achieve diverse and high-quality responses by selecting an answer from a small poo…