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Paper Citation Record · LEDGER

Empirical Research on Utilizing LLM-based Agents for Automated Bug Fixing via LangGraph

As of 10 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 1 inbound Pith citation observation for arXiv:2502.18465.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2502.18465 v1

Coverage vector

measured 9 of 9 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T04:37:16.682863Z

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T16:20:59.611197Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T16:21:03.428246Z

Reference resolution

9 of 9 outbound references displayed

  • verified exact0
  • verified fuzzy2
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2220cd6a-ba94-4fab-8084-9564896e7174 · outbound

This paper cites SWE-bench: Can Language Models Resolve Real-World GitHub Issues?.

Empirical Research on Utilizing LLM-based Agents for Automated Bug Fixing via LangGraph SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-10T04:37:16.649109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T04:37:16.649109Z digest=sha256:0bc64db8c46bd2c74d194c08e84a151185b84829aac973061aa09094101189d3

Observation 33aeee14-9ed4-4008-ba10-896630427d4f · outbound

This paper cites SWE-Bench+: Enhanced Coding Benchmark for LLMs.

Empirical Research on Utilizing LLM-based Agents for Automated Bug Fixing via LangGraph SWE-Bench+: Enhanced Coding Benchmark for LLMs

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-10T04:37:16.653625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T04:37:16.653625Z digest=sha256:1377a6e5c83467a3c715f8474c9be41d6163d3df15a1f66fbcda01bc3d0a39e6

Observation 02ede231-0afb-4e87-a604-841f74e656db · outbound

This paper cites An empirical study on llm-based agents for automated bug fixing.

Empirical Research on Utilizing LLM-based Agents for Automated Bug Fixing via LangGraph An empirical study on llm-based agents for automated bug fixing

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:37:16.788765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T04:37:16.657675Z digest=sha256:f01fdde6dcde5a2f093969cd060ea213e0106d0aa0b215aa1cdb611938413c09

Observation 467c48af-8f79-4006-aeb5-8c4bde53c655 · outbound

This paper cites MarsCode Agent: AI-native Automated Bug Fixing.

Empirical Research on Utilizing LLM-based Agents for Automated Bug Fixing via LangGraph MarsCode Agent: AI-native Automated Bug Fixing

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-10T04:37:16.661394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T04:37:16.661394Z digest=sha256:a78cef4b8064a71036902c4eb9be10df8fc91819df3d122ba87a35695aff65d8

Observation 43aaf7cd-5443-4523-9323-566aa794e4d5 · outbound

This paper cites Alibaba LingmaAgent: Improving Automated Issue Resolution via Comprehensive Repository Exploration.

Empirical Research on Utilizing LLM-based Agents for Automated Bug Fixing via LangGraph Alibaba LingmaAgent: Improving Automated Issue Resolution via Comprehensive Repository Exploration

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-10T04:37:16.665775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T04:37:16.665775Z digest=sha256:0223d2b65fda07265ccbe1cd28b5c0d26622f07b77be241d55429d1a2a2d33e7

Observation 38bebe3c-36b7-4115-b23c-0904ba520110 · outbound

This paper cites Autocoderover: Autonomous program improvement.

Empirical Research on Utilizing LLM-based Agents for Automated Bug Fixing via LangGraph Autocoderover: Autonomous program improvement

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:37:16.777362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T04:37:16.670717Z digest=sha256:60013825c448d84f949450703b70aece5648b8c9ebedaaf2ef23daffaeef0103

Observation 9323cea2-b834-4557-a467-128e769daeaf · outbound

This paper cites RepoGraph: Enhancing AI Software Engineering with Repository-level Code Graph.

Empirical Research on Utilizing LLM-based Agents for Automated Bug Fixing via LangGraph RepoGraph: Enhancing AI Software Engineering with Repository-level Code Graph

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-10T04:37:16.674928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T04:37:16.674928Z digest=sha256:1b83dce1d1ced9341395a7ba10a0f9450c7f1c3fe4213a9db5462c35c201ef7f

Observation ef0cd3bb-83e6-4cd4-bc44-62eb9c31dbbe · outbound

This paper cites , " * write output.state after.block = add.period write.

Empirical Research on Utilizing LLM-based Agents for Automated Bug Fixing via LangGraph , " * write output.state after.block = add.period write

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-10T04:37:16.678761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T04:37:16.678761Z digest=sha256:32dd171d584ddcda7707ade5aac0f0488c152a240a885051992b882e19068215

Observation 351668ac-4176-40d7-aa55-0b0fe303ab98 · outbound

This paper cites write newline.

Empirical Research on Utilizing LLM-based Agents for Automated Bug Fixing via LangGraph write newline

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T04:37:16.682863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T04:37:16.682863Z digest=sha256:9dd3a1fe1a7a8c9f4f0d5f845ad2a27c050c91f58c27ab3f533a026045471946

Pith citing papers

Observation f2b02e11-a5f4-425b-9eeb-31d6fc0e04ad · inbound

Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions cites this paper.

Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions Empirical Research on Utilizing LLM-based Agents for Automated Bug Fixing via LangGraph

Reference 120

Resolution
verified exact
local_arxiv, observed 2026-08-05T16:21:03.440755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T16:20:59.611197Z digest=sha256:672517b9d9345259bbf88879d7ca9d96bb95b5ac8dc184836583868a3e68d7ed