Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:42:05.472880Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 2 inbound Pith citation observations for arXiv:2506.13186.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:42:05.472880Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T15:06:55.050376Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-16T05:57:24.432794Z
79 of 79 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation b167f023-3aeb-4ead-87bb-3be516ef7ee1 · outbound
Empirical Evaluation of Large Language Models in Automated Program Repair The debugging mindset: Understanding the psychology of learning strategies leads to effective problem-solving skills
Reference 1
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Empirical Evaluation of Large Language Models in Automated Program Repair Genprog: A generic method for automatic software repair,
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Empirical Evaluation of Large Language Models in Automated Program Repair Nopol: Automatic repair of conditional statement bugs in java programs,
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Empirical Evaluation of Large Language Models in Automated Program Repair Staged program repair with condition synthesis,
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Empirical Evaluation of Large Language Models in Automated Program Repair Angelix: Scalable multiline program patch synthesis via symbolic analysis,
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Empirical Evaluation of Large Language Models in Automated Program Repair Astor: A program repair library for java,
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Empirical Evaluation of Large Language Models in Automated Program Repair Automatic patch generation by learning correct code,
Reference 9
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Empirical Evaluation of Large Language Models in Automated Program Repair Leveraging syntax-related code for automated program repair,
Reference 10
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Empirical Evaluation of Large Language Models in Automated Program Repair Precise condition synthesis for program repair,
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Empirical Evaluation of Large Language Models in Automated Program Repair Context-aware patch generation for better automated program repair,
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Empirical Evaluation of Large Language Models in Automated Program Repair Shaping program repair space with existing patches and similar code,
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Empirical Evaluation of Large Language Models in Automated Program Repair Avatar: Fixing semantic bugs with fix patterns of static analysis violations,
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Empirical Evaluation of Large Language Models in Automated Program Repair Practical program repair via bytecode mutation,
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Reference 21
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Empirical Evaluation of Large Language Models in Automated Program Repair Coconut: combining context-aware neural translation models using ensemble for program repair,
Reference 22
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Empirical Evaluation of Large Language Models in Automated Program Repair A syntax-guided edit decoder for neural program repair,
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Empirical Evaluation of Large Language Models in Automated Program Repair Cure: Code-aware neural machine translation for automatic program repair,
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Empirical Evaluation of Large Language Models in Automated Program Repair Neural program repair with execution-based backpropagation,
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Reference 30
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Reference 31
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Empirical Evaluation of Large Language Models in Automated Program Repair CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis
Reference 32
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Observation e5d92750-57d9-4d2c-a8aa-24c3189299a2 · outbound
Empirical Evaluation of Large Language Models in Automated Program Repair Available: https://proceedings.neurips.cc/paper files/ paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf
Reference 1901
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 59f72b53-4217-48de-9a4c-7f0376aba95d · outbound
Empirical Evaluation of Large Language Models in Automated Program Repair Available: https://proceedings.neurips.cc/paper/2022/ hash/9d5609613524ecf4f15af0f7b31abca4-Abstract-Conference.html
Reference 2022
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6827e5a6-d000-403b-bcf7-ea2837457152 · inbound
Automating Computational Reproducibility in Social Science: Comparing Prompt-Based and Agent-Based Approaches Empirical Evaluation of Large Language Models in Automated Program Repair
Reference 30
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 431b66bc-afd3-450e-bfd8-2ebc102b0793 · inbound
Semantic Drift in Bug Resolution: How Behavioral Signals Propagate from Reports to Tests and Patches Empirical Evaluation of Large Language Models in Automated Program Repair
Reference 41
Source-reported events for the cited work
Unavailable: canonical work link unavailable.