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20242026
most citedCan LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineering

54 citations · 54 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

MapSR: Prompt-Driven Land Cover Map Super-Resolution via Vision Foundation Models

Ruiqi Wang, Qi Yu, Jie Ma +1

High-resolution (HR) land-cover mapping is often constrained by the high cost of dense HR annotations. We revisit this problem from the perspective of map super-resolution, which e…

cs.SE2026

On the Effectiveness of Context Compression for Repository-Level Tasks: An Empirical Investigation

Jia Feng, Zhanyue Qin, Cuiyun Gao +4

Repository-level code intelligence tasks require large language models (LLMs) to process long, multi-file contexts. Such inputs introduce three challenges: crucial context can be o…

cs.SE2025

Benchmarking Code LLM-as-a-Judge via Constrained Perturbation and Calibration

Ruiqi Wang, Xinchen Wang, Cuiyun Gao +3

Code from LLM-assisted development may contain defects like API hallucinations, motivating the development of code evaluation metrics to assess such code before deployment. As conv…

cs.SE2025

An Empirical Study of Knowledge Distillation for Code Understanding Tasks

Ruiqi Wang, Zezhou Yang, Cuiyun Gao +2

Pre-trained language models (PLMs) have emerged as powerful tools for code understanding. However, deploying these PLMs in large-scale applications faces practical challenges due t…

cs.SE2025★ 54 cited

Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineering

Ruiqi Wang, Jiyu Guo, Cuiyun Gao +3

Recently, large language models (LLMs) have been deployed to tackle various software engineering (SE) tasks like code generation, significantly advancing the automation of SE tasks…

cs.SE2024

Game Rewards Vulnerabilities: Software Vulnerability Detection with Zero-Sum Game and Prototype Learning

Xin-Cheng Wen, Cuiyun Gao, Xinchen Wang +3

Recent years have witnessed a growing focus on automated software vulnerability detection. Notably, deep learning (DL)-based methods, which employ source code for the implicit acqu…