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Paper Citation Record · LEDGER

A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 30 inbound Pith citation observations for arXiv:2311.10372.

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

pith.paper-citation-record.v1
2311.10372 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 30 of 30 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:02:48.170023Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

20
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c6918eb6-5bf9-43b2-9a33-d66f8a1321c0 · inbound

CodePori: Large-Scale System for Autonomous Software Development Using Multi-Agent Technology cites this paper.

CodePori: Large-Scale System for Autonomous Software Development Using Multi-Agent Technology A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-05-24T03:58:51.367897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-24T03:58:32.556725Z digest=sha256:568f940c0335dff436f9ce6968f97b230397d9c19e25733d45a55b85a597691a

Observation 583e48e4-013e-4b21-9bdc-2addb7b93787 · inbound

A Survey on the Memory Mechanism of Large Language Model based Agents cites this paper.

A Survey on the Memory Mechanism of Large Language Model based Agents A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 41

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T07:21:39.798831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T07:21:39.440092Z digest=sha256:52abc46b5ce5512ac7bc499baff4edbf72373afc2e77acabc4c059086f60c8b6

Observation 21879bb5-1e9b-4382-9114-a3b7d8c6de5e · inbound

Are Decoder-Only Large Language Models the Silver Bullet for Code Search? cites this paper.

Are Decoder-Only Large Language Models the Silver Bullet for Code Search? A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 15

Resolution
metadata mismatch
arxiv_id, observed 2026-05-23T18:43:19.253516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T18:39:21.915976Z digest=sha256:126ab1c7ca6430f41c306d1b5f6eadf2c4d468fcabbdb0bc9d5aa41b02aeb4c6

Observation e7469eab-ea21-4a10-9f36-544021202550 · inbound

ELABORATION: A Comprehensive Benchmark on Human-LLM Competitive Programming cites this paper.

ELABORATION: A Comprehensive Benchmark on Human-LLM Competitive Programming A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 2023

Resolution
malformed identifier
no resolver link, observed 2026-08-07T15:02:48.170023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:02:48.170023Z digest=sha256:c6c5f4c17660f6d102fc2d5af3b153ce9d51aa1540bf7ede7fc993b86aa9af2d

Observation 2461a6aa-6f3f-4aad-bde2-41d8cacd2150 · inbound

CXXCrafter: An LLM-Based Agent for Automated C/C++ Open Source Software Building cites this paper.

CXXCrafter: An LLM-Based Agent for Automated C/C++ Open Source Software Building A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-07T13:46:10.670308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:46:10.670308Z digest=sha256:b9d94d8d76e8e36ea21c265f0d46382777f2e79d407a91ea4fd7464656e6b6cd

Observation b23e4a68-4c6b-4d67-93cf-3c1e4b6a136b · inbound

SimuGen: Multi-modal Agentic Framework for Constructing Block Diagram-Based Simulation Models cites this paper.

SimuGen: Multi-modal Agentic Framework for Constructing Block Diagram-Based Simulation Models A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T13:27:21.592008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:27:21.592008Z digest=sha256:c393f932790bbf2481a07757739502607c20a4c24dd60671568fad0fc46428a2

Observation 3db72a9d-bd24-4d35-8fa9-a0faeb46f18c · inbound

JsDeObsBench: Measuring and Benchmarking LLMs for JavaScript Deobfuscation cites this paper.

JsDeObsBench: Measuring and Benchmarking LLMs for JavaScript Deobfuscation A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-06T22:59:48.243202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:59:48.243202Z digest=sha256:d5abd0ca25b77cec69f1bf8fdd758011ab33cf3bebb60ea79801c676bf29fd27

Observation 5bd897d8-73bb-429f-ab20-c048a8d577ec · inbound

An AST-guided LLM Approach for SVRF Code Synthesis cites this paper.

An AST-guided LLM Approach for SVRF Code Synthesis A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T21:24:38.802024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:24:38.802024Z digest=sha256:66cba7e0333e61be59d8201095030084274b8f1bc74a62c7ad7ab35d3ddb53a7

Observation 484241d3-9e22-418d-9187-0a3cd6c63540 · inbound

Accelerating Automatic Program Repair with Dual Retrieval-Augmented Fine-Tuning and Patch Generation on Large Language Models cites this paper.

Accelerating Automatic Program Repair with Dual Retrieval-Augmented Fine-Tuning and Patch Generation on Large Language Models A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-06T17:44:51.793823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:44:51.793823Z digest=sha256:453e75983a881f1e3d6a8a9054e71b6d8973c03e309db18114101d15ac52f3cb

Observation dd6835c7-3303-4b0a-859d-e05e37add1d3 · inbound

Optimizing Token Choice for Code Watermarking: An RL Approach cites this paper.

Optimizing Token Choice for Code Watermarking: An RL Approach A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-05T19:46:12.352279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T19:46:12.352279Z digest=sha256:5ffaf8ea91e15e11e66ea2c0eb281f501038cc0a69ddb698f60036169df0c20f

Observation ab8c0954-3dec-41f5-9ce5-df54038fc232 · inbound

Human-Written vs. AI-Generated Code: A Large-Scale Study of Defects, Vulnerabilities, and Complexity cites this paper.

Human-Written vs. AI-Generated Code: A Large-Scale Study of Defects, Vulnerabilities, and Complexity A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-05T14:09:57.904741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:09:57.904741Z digest=sha256:d3f0f433d7a90a77d3e8154730cd8fbcbfe6b6f41b34b905de2e2d83c26c19cf

Observation 9692053e-9b35-49a4-9f95-df9613160f9b · inbound

GRACE: Graph-Guided Repository-Aware Code Completion through Hierarchical Code Fusion cites this paper.

GRACE: Graph-Guided Repository-Aware Code Completion through Hierarchical Code Fusion A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-05T04:48:40.018554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T04:48:40.018554Z digest=sha256:f66bcbafec856afd3cde3159767a6a4262cb93f45b61052f2d1492af5ca5c429

Observation 779fa3ab-8170-41c6-aafb-59ead279e3ae · inbound

SGAgent: Suggestion-Guided LLM-Based Multi-Agent Framework for Repository-Level Software Repair cites this paper.

SGAgent: Suggestion-Guided LLM-Based Multi-Agent Framework for Repository-Level Software Repair A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-02T20:17:27.097382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T20:17:27.097382Z digest=sha256:dc546497fdb1689946f93736ab0036ded44d7b5d9ec26fbe120afd682051ebb0

Observation 9dd07179-6e59-4b2f-814f-77740a938ec0 · inbound

Compiling Code LLMs into Lightweight Executables cites this paper.

Compiling Code LLMs into Lightweight Executables A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 82

Resolution
verified exact
arxiv_id, observed 2026-05-13T23:28:26.199234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T23:26:03.943399Z digest=sha256:0587d45e5ef61b84ac6329a27b0c32177bc503166b1bf77245222f745e188465

Observation 2207aa11-ad95-44ed-ba4f-40b220422a9a · inbound

Combining Static Code Analysis and Large Language Models Improves Correctness and Performance of Algorithm Recognition cites this paper.

Combining Static Code Analysis and Large Language Models Improves Correctness and Performance of Algorithm Recognition A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 32

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T19:33:10.152765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T19:31:51.501833Z digest=sha256:87757727db4f8f9b6269db06b02f04929ec1e19f46c3e2cfea7b9090088eff79

Observation e1d2b2f4-3a0a-4f7e-8e06-a229c1830880 · inbound

Can LLMs Deobfuscate Binary Code? A Systematic Analysis of Large Language Models into Pseudocode Deobfuscation cites this paper.

Can LLMs Deobfuscate Binary Code? A Systematic Analysis of Large Language Models into Pseudocode Deobfuscation A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 70

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T05:35:59.832296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T18:02:53.996840Z digest=sha256:b6d320aaa4508002342386149a903eaf6c63e409f14026cc597fc5094dc4ee6d

Observation 04d3fafd-a942-48d8-a9a9-a4082933ab89 · inbound

Leveraging Mathematical Reasoning of LLMs for Efficient GPU Thread Mapping cites this paper.

Leveraging Mathematical Reasoning of LLMs for Efficient GPU Thread Mapping A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-11T08:30:58.301376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T16:35:33.392202Z digest=sha256:ff26126b6a37b56073a35757604d606151582f8a5b6ade5a2694c458a99efe98

Observation c2898f2c-3f77-494d-81ed-e80edfb2fcf0 · inbound

LLM-Based Multi-Agent Systems for Code Generation: A Multi-Vocal Literature Review cites this paper.

LLM-Based Multi-Agent Systems for Code Generation: A Multi-Vocal Literature Review A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 70

Resolution
verified exact
arxiv_id, observed 2026-05-15T19:56:33.803554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T19:52:49.324500Z digest=sha256:0d07b8c13da59fddeee54d7d2bfbbdb1e1b192792c4effd8eaf62284712bd212

Observation e2241d6a-4db0-4322-bae4-21e7eb7cdd8a · inbound

AI-Generated Smells: An Analysis of Code and Architecture in LLM and Agent-Driven Development cites this paper.

AI-Generated Smells: An Analysis of Code and Architecture in LLM and Agent-Driven Development A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:50:39.886991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T18:06:00.379846Z digest=sha256:34987fdf784b36cb6ae6ad10701e1113f53935cb64b4c08dd2d0b3d25cf85195

Observation d77afdfd-1334-4a8a-9d02-53b0f3f74d2e · inbound

Reversa: A Reverse Documentation Engineering Framework for Converting Legacy Software into Operational Specifications for AI Agents cites this paper.

Reversa: A Reverse Documentation Engineering Framework for Converting Legacy Software into Operational Specifications for AI Agents A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 44

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T09:03:09.773723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T08:58:32.951138Z digest=sha256:785610e243aa18aa7ea07b246b587acfdfa90a4cc786b9a93abf7ba9a535a1c7

Observation bd747422-143c-4e3f-946a-7a8bf8cd8174 · inbound

Understanding Conversational Patterns in Multi-agent Programming: A Case Study on Fibonacci Game Development cites this paper.

Understanding Conversational Patterns in Multi-agent Programming: A Case Study on Fibonacci Game Development A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-06-30T15:04:46.375420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T14:57:40.568265Z digest=sha256:9b41f30a47b4ec5d600d184cdcaa218768b078d2776d817aa7df5ffcb9688491

Observation 16e5b4e7-2264-4dad-a9d2-28ecac59cdee · inbound

A Tertiary Review of Large Language Model-Based Code Generating Tasks: Trends, Challenges, and Future Directions cites this paper.

A Tertiary Review of Large Language Model-Based Code Generating Tasks: Trends, Challenges, and Future Directions A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 111

Resolution
verified exact
arxiv_id, observed 2026-06-29T20:53:58.477007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T20:48:19.988304Z digest=sha256:9b2464109d2e383233e7fdae6c6931fc7e87adb03085f8253e5bfe9ef189665c

Observation 236ed032-871e-4016-9b14-f3ee2f4bbecb · inbound

DeltaMCP: Incremental Regeneration via Spec-Aware Transformation for MCP servers cites this paper.

DeltaMCP: Incremental Regeneration via Spec-Aware Transformation for MCP servers A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T11:13:21.003179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T11:05:34.514376Z digest=sha256:44ed7588d3f84f68e126c65334af7db70cc71a5dcd4c164498dd771e23439cbf

Observation 2e5d75cd-1663-4880-b070-1057539ecdb6 · inbound

PassNet: Scaling Large Language Models for Graph Compiler Pass Generation cites this paper.

PassNet: Scaling Large Language Models for Graph Compiler Pass Generation A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 5

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T07:53:13.233925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T07:53:06.859337Z digest=sha256:942d3c166c1c408bb4e554262da5f334eee66367c81aab4d030908d67441d0cf

Observation 990d21c5-f1b0-4b37-af6c-98b5cf2b7757 · inbound

Qiskit Code Migration with LLMs cites this paper.

Qiskit Code Migration with LLMs A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 107

Resolution
verified exact
arxiv_id, observed 2026-06-26T16:29:35.643648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-26T16:24:25.357338Z digest=sha256:291d131aa4160a778378dae754fee487858f83150e1c6b498397a0bcd98000c0

Observation 3e269805-5883-4fc1-b26d-39e6ea4922d8 · inbound

Test Case Selection for Deep Neural Networks: A Replication Study on LLMs for Code cites this paper.

Test Case Selection for Deep Neural Networks: A Replication Study on LLMs for Code A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 75

Resolution
verified exact
arxiv_id, observed 2026-06-29T00:52:55.664336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T00:47:54.236329Z digest=sha256:f680d13e93d0571135a27e3ddc289f3fa877806024bf4d0382c1916da551341d

Observation 20106659-481f-487f-90cf-9f6fd8e23a8c · inbound

Plainbook: Data Science, in Plain Language cites this paper.

Plainbook: Data Science, in Plain Language A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-07-11T03:17:52.195751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-11T03:10:06.679816Z digest=sha256:c416655a60863d7154b2f055338c87bcbb36928891d45e3e42e6fc93406d74fd

Observation 0e0c0f02-67d5-4670-bfa9-b181f08b84ac · inbound

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents cites this paper.

PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-01T14:11:54.805534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:11:54.805534Z digest=sha256:4924de8263f4288dc3161b5b7d01fd868555f98d100d9b4c97d5c98f9a55d726

Observation d8e0b6e0-d592-4371-9c03-400dc36c76cd · inbound

CLEAR: Causal Context-Based Agentic Reasoning for Vulnerability Detection cites this paper.

CLEAR: Causal Context-Based Agentic Reasoning for Vulnerability Detection A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T01:06:29.039986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T01:06:29.039986Z digest=sha256:8a12a08e0e122f3da491fb22aeb5af95d870e662c97fd18fa316f1c6535be97e

Observation b7230266-38bd-496d-aedf-3777a7b95d67 · inbound

Is Inter-Seed Cross-Play Enough? Evaluating the Robustness of Zero-Shot Coordination Algorithms to Implementation Details cites this paper.

Is Inter-Seed Cross-Play Enough? Evaluating the Robustness of Zero-Shot Coordination Algorithms to Implementation Details A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 149

Resolution
unresolved
no resolver link, observed 2026-08-05T15:25:39.975070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:25:39.975070Z digest=sha256:16b4954de738a47f427ce266008474400086fc7b1406aa954eaa1cad4a137f10