Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T19:09:34.399866Z
Paper Citation Record · LEDGER
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis
As of 15 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2507.06463.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
25 of 25 outbound references displayed
- verified exact0
- verified fuzzy13
- unresolved12
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation ba7f6e73-fcc7-46a1-a371-b00ae8a00319 · outbound
This paper cites A survey on evaluation of large language models,.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis A survey on evaluation of large language models,
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:09:32.964352Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 78add78e-708c-4197-8756-aa2e3ef61741 · outbound
This paper cites CodeT: Code Generation with Generated Tests.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis CodeT: Code Generation with Generated Tests
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:09:33.045458Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9a5b1af6-ca8f-4586-87fc-4b05d7191f9a · outbound
This paper cites Is your code generated by ChatGPT really correct? rigorous evaluation of large language models for code generation,.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis Is your code generated by ChatGPT really correct? rigorous evaluation of large language models for code generation,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:09:36.332727Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 993294e3-f724-4824-9305-34f4c5531b9c · outbound
This paper cites CodeJudge: Evaluating Code Generation with Large Language Models.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis CodeJudge: Evaluating Code Generation with Large Language Models
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:09:33.177676Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 56073c54-b086-4922-9c9d-4d69f8c17269 · outbound
This paper cites An empirical evaluation of GitHub copilot’s code suggestions,.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis An empirical evaluation of GitHub copilot’s code suggestions,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:09:36.194276Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation f06185d4-b840-46c7-a58b-f940fb37f5b6 · outbound
This paper cites Large language models of code fail at completing code with potential bugs,.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis Large language models of code fail at completing code with potential bugs,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:09:36.160801Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation da2619a2-6570-4b93-ab5e-3db5659a395d · outbound
This paper cites Bugs in large language models generated code: An empirical study,.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis Bugs in large language models generated code: An empirical study,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:09:36.048114Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 2936ff44-e4aa-4ca5-ade9-14fbb27c56ce · outbound
This paper cites Large language models and simple, stupid bugs,.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis Large language models and simple, stupid bugs,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:09:35.866329Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 4e890f62-5a39-41a7-a31f-7ddcd66cd7f1 · outbound
This paper cites Evaluating Large Language Models Trained on Code.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis Evaluating Large Language Models Trained on Code
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:09:33.493159Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ab95d412-92a2-45c6-9b76-29ed5f2973e7 · outbound
This paper cites Program Synthesis with Large Language Models.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis Program Synthesis with Large Language Models
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:09:33.561579Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e2bdff79-83aa-40b0-a4ee-49111c52fb73 · outbound
This paper cites EffiBench: Benchmarking the efficiency of automatically generated code,.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis EffiBench: Benchmarking the efficiency of automatically generated code,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:09:35.702841Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 2dec1611-4a8a-4c52-a7a3-d945316cc130 · outbound
This paper cites How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:09:33.646855Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c134dd97-fc0f-4edb-addd-e1dad793e0b6 · outbound
This paper cites Comparing Human and LLM Generated Code: The Jury is Still Out!.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis Comparing Human and LLM Generated Code: The Jury is Still Out!
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:09:33.701678Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 12179005-66ad-4c07-82e8-74ae8c614eb2 · outbound
This paper cites Mercury: A Code Efficiency Benchmark for Code Large Language Models.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis Mercury: A Code Efficiency Benchmark for Code Large Language Models
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:09:33.758152Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7a20717e-57ae-4104-a54e-1c4300066632 · outbound
This paper cites On evaluating the efficiency of source code generated by LLMs,.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis On evaluating the efficiency of source code generated by LLMs,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:09:35.644735Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 1cb1e528-f75e-4bfe-b75c-94514f89637c · outbound
This paper cites Evaluating Language Models for Efficient Code Generation.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis Evaluating Language Models for Efficient Code Generation
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:09:33.889386Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fe90a91a-e20b-49c6-865f-7ab341d7b353 · outbound
This paper cites FRANC: A lightweight framework for high-quality code generation,.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis FRANC: A lightweight framework for high-quality code generation,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:09:35.622557Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 47f5486b-76b8-41db-82a6-80dd5d887dcf · outbound
This paper cites Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:09:34.032611Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5406a1ba-6d88-42f0-83ba-a0f6570c21ac · outbound
This paper cites LLM4EFFI: Leveraging Large Language Models to Enhance Code Efficiency and Correctness.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis LLM4EFFI: Leveraging Large Language Models to Enhance Code Efficiency and Correctness
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:09:34.091736Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 42aa8b5b-43ed-4eff-9ac1-c6246f0184cf · outbound
This paper cites ECCO: Can We Improve Model-Generated Code Efficiency Without Sacrificing Functional Correctness?.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis ECCO: Can We Improve Model-Generated Code Efficiency Without Sacrificing Functional Correctness?
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:09:34.151265Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0e0344fe-e463-462e-8e40-0d8c5196bd75 · outbound
This paper cites Fast triangle counting,.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis Fast triangle counting,
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:09:35.437433Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 80e5aab6-f105-4b9b-ac5a-1687417224df · outbound
This paper cites Finding, counting and listing all triangles in large graphs, an experimental study,.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis Finding, counting and listing all triangles in large graphs, an experimental study,
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:09:35.280137Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b6b2f5b3-0a65-445a-a060-caf308595ca9 · outbound
This paper cites Algorithmic aspects of triangle-based network analysis,.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis Algorithmic aspects of triangle-based network analysis,
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:09:34.989136Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 362b0146-03bb-4cf9-a5cc-b2242258c171 · outbound
This paper cites Triangle counting through cover-edges,.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis Triangle counting through cover-edges,
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:09:34.719709Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation a6895ef2-917a-45b6-a7ca-3ec3512ef9e8 · outbound
This paper cites R-MAT: A recursive model for graph mining,.
Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis R-MAT: A recursive model for graph mining,
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:09:34.600469Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Pith citing papers
No inbound Pith citation observations are available.