1 citations · 1 across the 4 of their papers we have counts for
6 papers
Speculative Forking: Turning Idle Wait into Parallel Exploration for Repository Environment Setup
Yuling Shi, Mingchu Zhong, Zhensu Sun +8
Before developers can use a software project, they must first get it to run. This often requires installing the right language runtime, system packages, build tools, and test comma…
Pairing Matters: Performance, Failures, and Efficiency in Lightweight Coding Agents
Lu Zhao, Christopher M. Poskitt, David Lo
Self-hosting coding agents is often necessary for software-engineering teams that must keep proprietary code and development traces within controlled infrastructure. Lightweight, o…
EarlyEval: Cheaper Agent Evaluation via Early Outcome Prediction
Yuling Shi, Zhensu Sun, Junsen Dong +3
Evaluating LLM agents is essential for guiding their development, yet it has grown prohibitively expensive: a single pass of a frontier model over an agentic benchmark can cost hun…
Are Performance-Optimization Benchmarks Reliably Measuring Coding Agents?
Zhi Chen, Zhensu Sun, Yuling Shi +2
Repository-level performance-optimization benchmarks such as GSO, SWE-Perf and SWE-fficiency evaluate coding agents by applying patches to real repositories and comparing runtime a…
Rethinking the Value of Agent-Generated Tests for LLM-Based Software Engineering Agents
Zhi Chen, Zhensu Sun, Yuling Shi +4
Large Language Model (LLM) code agents increasingly resolve repository-level issues by iteratively editing code, invoking tools, and validating candidate patches. In these workflow…
Seeing is Coding: On the Effectiveness of Vision Language Models in Code Understanding
Yuling Shi, Chaoxiang Xie, Zhensu Sun +7
Large Language Models (LLMs) have achieved remarkable success in source code understanding, yet as software systems grow in scale, computational efficiency has become a critical bo…