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Mark Harman

ACL 2026×2KDD 2026NeurIPS 2026评测与基准智能体与工具代码对齐与偏好安全
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0 一作 · 4 篇 · ACL 2026 / KDD 2026 / NeurIPS 2026

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2026 顶会论文

4
作者位次 #2/7ACL 2026Findings· Findings of ACL

A Study of LLM s’ Preferences for Libraries and Programming Languages

Lukas Twist · Mark Harman · Don Syme · Joost Noppen · Helen Yannakoudakis · Detlef Nauck · Jie M. Zhang

摘要

Despite the rapid progress of large language models (LLMs) in code generation, existing evaluations focus on functional correctness or syntactic validity, overlooking how LLMs make critical design choices such as which library or programming language to use.To fill this gap, we perform the first...

评测与基准代码对齐与偏好OpenReview 项目页
作者位次 #4/7ACL 2026Findings· Findings of ACL

EET : Experience-Driven Early Termination for Cost-Efficient Software Engineering Agents

Yaoqi Guo · Ying Xiao · Jie M. Zhang · Mark Harman · Yiling Lou · Yang Liu · Zhenpeng Chen

摘要

Software engineering (SE) agents powered by large language models are increasingly adopted in practice, yet they often incur substantial monetary cost. We introduce EET, an experience-driven early termination approach that reduces the cost of SE agents while preserving task performance. EET extra...

评测与基准代码智能体与工具OpenReview 项目页

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