3 papers
cs.SE2026
SpIDER: Spatially Informed Dense Embedding Retrieval for Software Issue Localization
Shravan Chaudhari, Rahul Thomas Jacob, Mononito Goswami +3
Retrieving code functions, classes or files that are relevant in order to solve a given user query, bug report or feature request from large codebases is a fundamental challenge fo…
cs.CL2025
Textual Gradients are a Flawed Metaphor for Automatic Prompt Optimization
Daniel Melcer, Qi Chen, Wen-Hao Chiang +3
A well-engineered prompt can increase the performance of large language models; automatic prompt optimization techniques aim to increase performance without requiring human effort…
cs.SE2025
SWE-PolyBench: A multi-language benchmark for repository level evaluation of coding agents
Muhammad Shihab Rashid, Christian Bock, Yuan Zhuang +10
Coding agents powered by large language models have shown impressive capabilities in software engineering tasks, but evaluating their performance across diverse programming languag…