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From the 1 of 8 linked papers with an AI index.

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8 papers

cs.SE2026

Retrieval-Oriented Code Representations in Agentic Bug Localization

Genevieve Caumartin, Tse-Hsun, Chen +1

The paper evaluates how different code representations, including LLM-generated textual summaries, affect the effectiveness and cost of file-level bug localization, finding that ro…

cs.SE2026

Bug Report Specification Refinement with Trajectory Guidance for Automated Program Repair

S M Farah Al Fahim, Md Nakhla Rafi, Md Ahasanuzzaman +5

Bug reports serve as task specifications for repository-level automated program repair (APR) agents, but they often describe only the observed failure and omit repair-relevant info…

cs.SE2026

Rethinking Code Performance Benchmarks for LLMs

Nhat Minh Le, Yisen Xu, Zhijie Wang +2

Many function-level performance benchmarks have been proposed to evaluate whether large language models (LLMs) can generate efficient programs. However, results on these benchmarks…

cs.SE2026

LogSemFuse: Semantic Evidence Fusion for Explainable Log Anomaly Detection

Hassan Jabri, Zeyang Ma, Zhijie Wang +1

Log anomaly detection is critical for reliability monitoring and failure diagnosis in modern software systems. Existing model-based detectors provide useful anomaly signals, but th…

cs.AI2026

FALAT: Tracing Failures in LLM Agent Trajectories via Dependency-Guided Search

Md Nakhla Rafi, Md Ahasanuzzaman, Dong Jae Kim +2

LLM-based agents increasingly solve complex tasks through long trajectories involving reasoning steps, tool calls, and inter-agent communication. However, when these agents fail, i…

cs.SE2026

Probe to Generate: Program Variant-Guided Test Augmentation for Repository-Level Repair Benchmarks

Chenglin Li, Yisen Xu, Zehao Wang +3

Test-based benchmarks such as SWE-bench have become a standard basis for evaluating automated issue resolution agents, deeming a patch correct if it passes a provided regression te…