Paper Citation Record · LEDGER

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators

As of 15 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 11 inbound Pith citation observations for arXiv:2508.09101.

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

pith.paper-citation-record.v1
2508.09101 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T21:18:29.153977Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T15:13:50.935010Z

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

30 of 30 outbound references displayed

verified exact1
verified fuzzy2
unresolved27
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 404202ab-2ac9-4e89-8da3-dda9575e996a · outbound

This paper cites SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:26.079582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f4636e5-23dd-41ba-983f-f6bc70d50431 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators Evaluating Large Language Models Trained on Code

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:26.382315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88c0a9ab-50c2-47c8-baa9-c206e77a5ff7 · outbound

This paper cites DeepSeek-V3 Technical Report.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators DeepSeek-V3 Technical Report

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:26.487023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc1b5865-60ff-4b34-ace1-859c6c1ec486 · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:26.684754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e425ee9-5964-4615-9b3b-667575a21e79 · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:26.806206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa5a5a28-0ac1-4775-851b-8c5c793c757c · outbound

This paper cites CodeEditorBench: Evaluating Code Editing Capability of Large Language Models.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators CodeEditorBench: Evaluating Code Editing Capability of Large Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:26.902628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00d38d5b-e319-42f8-aae5-5374c6abcd54 · outbound

This paper cites OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:27.044990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6975957d-e735-491d-823a-f8a3aa8a3483 · outbound

This paper cites A Survey on Large Language Models for Code Generation.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators A Survey on Large Language Models for Code Generation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:27.251061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67f9ac42-4e66-4c4a-9d08-e37b918d8067 · outbound

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

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:27.367469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 374da8da-6e88-42f5-a76b-56d2633b4d27 · outbound

This paper cites Kimi K2: Open Agentic Intelligence.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators Kimi K2: Open Agentic Intelligence

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:27.496436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 286b0d4e-c561-4888-9959-9117a668303d · outbound

This paper cites doi: 10.1126/science.abq1158.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators doi: 10.1126/science.abq1158

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:27.605502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6400a4c-50e6-481e-bee3-ff5cc6e04de4 · outbound

This paper cites HumanEval-XL: A Multilingual Code Generation Benchmark for Cross-lingual Natural Language Generalization.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators HumanEval-XL: A Multilingual Code Generation Benchmark for Cross-lingual Natural Language Generalization

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:27.684747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17e42d19-1e94-48f3-aa19-8c9786923d78 · outbound

This paper cites CodeElo: Benchmarking Competition-level Code Generation of LLMs with Human-comparable Elo Ratings.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators CodeElo: Benchmarking Competition-level Code Generation of LLMs with Human-comparable Elo Ratings

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:27.805253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89d7ccf0-3ccd-4544-97a7-104087f96718 · outbound

This paper cites Qwen2.5 Technical Report.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators Qwen2.5 Technical Report

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:27.886461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f91e24b2-3419-459c-81de-f8f935449a3f · outbound

This paper cites Seed-Coder: Let the Code Model Curate Data for Itself.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators Seed-Coder: Let the Code Model Curate Data for Itself

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:27.964338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 198c1050-280b-453d-ac36-ed6b2c83b42c · outbound

This paper cites Kaixin Wang, Tianlin Li, Xiaoyu Zhang, Chong Wang, Weisong Sun, Yang Liu, and Bin Shi.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators Kaixin Wang, Tianlin Li, Xiaoyu Zhang, Chong Wang, Weisong Sun, Yang Liu, and Bin Shi

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:28.059166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f29a7ea-cecd-4d38-b937-1b72fb680195 · outbound

This paper cites WaveCoder: Widespread And Versatile Enhancement For Code Large Language Models By Instruction Tuning.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators WaveCoder: Widespread And Versatile Enhancement For Code Large Language Models By Instruction Tuning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:28.245399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95dcbbed-88af-4ba4-8607-d4235f3ba155 · outbound

This paper cites Multi-SWE-bench: A Multilingual Benchmark for Issue Resolving.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators Multi-SWE-bench: A Multilingual Benchmark for Issue Resolving

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:28.374667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71b73a86-1486-4778-a990-b970b84c1c16 · outbound

This paper cites NaturalCodeBench: Examining Coding Performance Mismatch on HumanEval and Natural User Prompts.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators NaturalCodeBench: Examining Coding Performance Mismatch on HumanEval and Natural User Prompts

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:28.467608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd3f18c5-5e10-43a6-ad1f-60500951a413 · outbound

This paper cites doi: 10.18653/v1/2024.findings-acl.762.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators doi: 10.18653/v1/2024.findings-acl.762

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:28.544826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b367fcbe-3f42-4b12-972c-c2789e8c36da · outbound

This paper cites LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming?.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming?

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:28.722411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d73353c-3220-4953-9140-324f45194dad · outbound

This paper cites RefineCoder: Iterative Improving of Large Language Models via Adaptive Critique Refinement for Code Generation.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators RefineCoder: Iterative Improving of Large Language Models via Adaptive Critique Refinement for Code Generation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:28.851648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13979a02-a595-4766-af05-c8b0caeed694 · outbound

This paper cites OIBench: Benchmarking Strong Reasoning Models with Olympiad in Informatics.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators OIBench: Benchmarking Strong Reasoning Models with Olympiad in Informatics

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-05T21:18:29.439278Z

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 96c61cb4-bdfe-4e48-a81e-6586fbc8ad55 · outbound

This paper cites main.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators __main__

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:18:45.388228Z

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 8eefd89b-f45a-4c78-80ed-437b17880e0f · outbound

This paper cites 22 # Code Benchmark Construction TaskIn order to build the code benchmark, I need you to help me create a Python function, as well as two test functions.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators 22 # Code Benchmark Construction TaskIn order to build the code benchmark, I need you to help me create a Python function, as well as two test functions

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:18:45.076736Z

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 93d537fe-9023-497f-ac4f-9767c15470aa · outbound

This paper cites Qwen3 Technical Report.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators Qwen3 Technical Report

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:28.164750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcc817ce-4445-42ca-aa1a-d741bb9ca7ad · outbound

This paper cites Program Synthesis with Large Language Models.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators Program Synthesis with Large Language Models

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:26.165195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97742432-eee2-45d9-8f71-b792fa671509 · outbound

This paper cites MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:26.294753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70e884f0-4d1e-45ba-8361-a00a8099eb0a · outbound

This paper cites DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:26.575634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5114ecfe-fb52-4e44-8466-be759840ff37 · outbound

This paper cites OpenCodeInstruct: A Large-scale Instruction Tuning Dataset for Code LLMs.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators OpenCodeInstruct: A Large-scale Instruction Tuning Dataset for Code LLMs

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:25.994910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 7371962a-864c-4fe9-b8c9-13480715b815 · inbound

From Prompt Optimization to Multi-Dimensional Credibility Evaluation: Enhancing Trustworthiness of Chinese LLM-Generated Liver MRI Reports -- with Preliminary Extension to Lung Cancer cites this paper.

From Prompt Optimization to Multi-Dimensional Credibility Evaluation: Enhancing Trustworthiness of Chinese LLM-Generated Liver MRI Reports -- with Preliminary Extension to Lung Cancer AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T08:03:36.759783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c58ae96-276a-4872-823c-8b0dc95a06ac · inbound

SkillFlow:Benchmarking Lifelong Skill Discovery and Evolution for Autonomous Agents cites this paper.

SkillFlow:Benchmarking Lifelong Skill Discovery and Evolution for Autonomous Agents AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:21:27.166102Z

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 047e65da-4768-4396-9fd1-9824a011065d · inbound

BenchCAD: A Comprehensive, Industry-Standard Benchmark for Programmatic CAD cites this paper.

BenchCAD: A Comprehensive, Industry-Standard Benchmark for Programmatic CAD AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T06:56:26.856757Z

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 73863823-1d47-4baa-98a7-64b200170ad5 · inbound

BenchCAD: A Comprehensive, Industry-Standard Benchmark for Programmatic CAD cites this paper.

BenchCAD: A Comprehensive, Industry-Standard Benchmark for Programmatic CAD AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T03:02:10.397601Z

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 b6d6a3cd-23bd-4de5-b7da-61bbe650cd73 · inbound

PerfCodeBench: Benchmarking LLMs for System-Level High-Performance Code Optimization cites this paper.

PerfCodeBench: Benchmarking LLMs for System-Level High-Performance Code Optimization AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T18:03:10.102773Z

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 20d73053-a8b1-4e43-9d1c-3281bf908ec5 · inbound

PBT-Bench: Benchmarking AI Agents on Property-Based Testing cites this paper.

PBT-Bench: Benchmarking AI Agents on Property-Based Testing AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-19T17:27:41.334004Z

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 6ce5e85f-b918-4633-a49a-516fb707b71b · inbound

PBT-Bench: Benchmarking AI Agents on Property-Based Testing cites this paper.

PBT-Bench: Benchmarking AI Agents on Property-Based Testing AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-21T07:59:50.106865Z

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 497e3519-f1de-4a52-9bd7-b0c5b14b951f · inbound

PBT-Bench: Benchmarking AI Agents on Property-Based Testing cites this paper.

PBT-Bench: Benchmarking AI Agents on Property-Based Testing AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:47.101402Z

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 8bed6de6-6e17-4131-9582-0a657bbfb095 · inbound

Code-QA-Bench: Separating Code Reasoning from Documentation Memorization in Repository-Level QA cites this paper.

Code-QA-Bench: Separating Code Reasoning from Documentation Memorization in Repository-Level QA AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T07:03:12.926179Z

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 3bdce69e-548b-480a-8975-a62cb8b0a0b5 · inbound

PERFOPT-Bench: Evaluating Coding Agents on Software Performance Optimization cites this paper.

PERFOPT-Bench: Evaluating Coding Agents on Software Performance Optimization AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-07-10T19:57:33.806970Z

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 452afdc8-54b1-40b5-894c-937eddea0652 · inbound

Cross-Domain Hybrid OPD for Generalizable Search Agents cites this paper.

Cross-Domain Hybrid OPD for Generalizable Search Agents AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T15:13:50.935010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.