LogicLoc combines LLMs with Datalog to achieve accurate repo-level code localization without relying on keyword shortcuts in benchmarks.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=
5 Pith papers cite this work, alongside 2 external citations. Polarity classification is still indexing.
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Pith papers citing it
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external citations · OpenAlex
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2026 5representative citing papers
Loc2Repair framework evaluation finds that file-level localization boosts LLM repo repair resolved rates by up to 7.7 percentage points on SWE-bench Verified.
SHERLOC introduces a training-free structured localization method that achieves SOTA accuracy on SWE-Bench and boosts repair agent resolve rates by 5.95 pp while reducing token use.
A multi-granularity program graph with intra-procedural def-use edges and a data-flow slicing tool raises SWE-agent resolve rate on SWE-bench Lite by 4.7 points under a fixed open-source backbone.
An empirical study finds that injecting call/inheritance topology as comments improves LLM code agent localization by 2.2pp, shortens trajectories by 1.6 rounds, and halves run-to-run variance on medium repositories via a deterministic anchoring effect.
citing papers explorer
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Neurosymbolic Repo-level Code Localization
LogicLoc combines LLMs with Datalog to achieve accurate repo-level code localization without relying on keyword shortcuts in benchmarks.
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Loc2Repair: A Framework for Evaluating the Impact of File-Level Issue Localization in Repo-Level LLM Repair
Loc2Repair framework evaluation finds that file-level localization boosts LLM repo repair resolved rates by up to 7.7 percentage points on SWE-bench Verified.
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SHERLOC: Structured Diagnostic Localization for Code Repair Agents
SHERLOC introduces a training-free structured localization method that achieves SOTA accuracy on SWE-Bench and boosts repair agent resolve rates by 5.95 pp while reducing token use.
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ARISE: A Repository-level Graph Representation and Toolset for Agentic Program Repair and Fault Localization
A multi-granularity program graph with intra-procedural def-use edges and a data-flow slicing tool raises SWE-agent resolve rate on SWE-bench Lite by 4.7 points under a fixed open-source backbone.
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How Much Static Structure Do Code Agents Need? A Study of Deterministic Anchoring
An empirical study finds that injecting call/inheritance topology as comments improves LLM code agent localization by 2.2pp, shortens trajectories by 1.6 rounds, and halves run-to-run variance on medium repositories via a deterministic anchoring effect.