Pith. sign in

Paper Citation Record · LEDGER

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms

As of 7 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2607.26083.

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

pith.paper-citation-record.v1
2607.26083 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-30T11:33:02.799819Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

33 of 33 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved33
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d0266842-3cbd-4a12-9ae3-2b36c7a77fac · outbound

This paper cites Ai agentic programming: A survey of techniques, challenges, and opportunities,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Ai agentic programming: A survey of techniques, challenges, and opportunities,

Reference 1

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:00.316817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:00.316817Z digest=sha256:bb867e4e08daea5dd4e7bb470c52c18ca49e893608a0fbbf51cdcb4d70ec0189

Observation c9a946e5-6785-4226-a3a6-506feb173813 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Evaluating Large Language Models Trained on Code

Reference 2

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:00.511508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:00.511508Z digest=sha256:2888cab7679f10f0e51877c791bf5827b10235690ce418d636c20324607b3341

Observation 3a5bbe0b-085e-4902-a926-df5b41b54f27 · outbound

This paper cites Program Synthesis with Large Language Models.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Program Synthesis with Large Language Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:00.623944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:00.623944Z digest=sha256:ca2dcaaf5ce33886dc350b1c8abc0083fa4cab5bc580a42006125c7a9b5aaf9a

Observation eb6613a4-338d-4d19-b260-3ff0e8859263 · outbound

This paper cites DS-1000: A natural and reliable benchmark for data science code generation,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms DS-1000: A natural and reliable benchmark for data science code generation,

Reference 4

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:00.704400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:00.704400Z digest=sha256:74aacd320e3c105e57cc08b97ea653cb829e12a07760f79f303bd9bee70dff63

Observation 4786bf19-892b-45d0-b334-a5e2fed132a3 · outbound

This paper cites Multipl-e: A scalable and polyglot approach to benchmarking neural code generation,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Multipl-e: A scalable and polyglot approach to benchmarking neural code generation,

Reference 5

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:00.796396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:00.796396Z digest=sha256:62689d5ca769b97146b14fff2d386b2f36cf29181f47b016fc1f24a594405cfa

Observation 2a5c60b8-a31b-45ea-a20e-e9ae1553e651 · outbound

This paper cites A Survey on Code Generation with LLM-based Agents.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms A Survey on Code Generation with LLM-based Agents

Reference 6

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:00.844872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:00.844872Z digest=sha256:aeffe44ec9ce0faaced7e9f1e00dc3cb4c70fb18d6e8802a4396b500d9bca303

Observation 02bfa65b-3558-4bf0-a070-68280ccb00e0 · outbound

This paper cites How efficient is llm-generated code? a rigorous & high-standard benchmark,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms How efficient is llm-generated code? a rigorous & high-standard benchmark,

Reference 7

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:00.910677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:00.910677Z digest=sha256:3cb795c99ec0ebc148ff71bfd1e67669a1322ed4780430371f26a6f8babaacec

Observation 09ee3ab7-02e7-4bde-9ebb-6ffbc784b800 · outbound

This paper cites Lm4hpc: Towards effective language model appli- cation in high-performance computing,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Lm4hpc: Towards effective language model appli- cation in high-performance computing,

Reference 8

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:00.967144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:00.967144Z digest=sha256:5cf41b5ee58c0070fcb9272959327e04df3b5e8f849107ed7cb6690b640e47bd

Observation b5bee89a-30f2-475d-b7e4-25341ed3fc85 · outbound

This paper cites Scope is all you need: Transforming LLMs for HPC Code.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Scope is all you need: Transforming LLMs for HPC Code

Reference 9

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:01.031055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:01.031055Z digest=sha256:31b5cc4f0d2ba2ef31ec8cb0d24611593255326670c5836bc3cbb84d1758180e

Observation 8ab7303f-77a6-4ca8-8417-3480d7255519 · outbound

This paper cites HPC-Coder: Modeling Parallel Programs using Large Language Models.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms HPC-Coder: Modeling Parallel Programs using Large Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:01.120179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:01.120179Z digest=sha256:f746e5711d2c7ecadd56e9d7df23ec8385cf7d55eb812d8f3566349af6afb986

Observation 47243d9f-5c08-4eb2-81c0-5325847bde86 · outbound

This paper cites Ompgpt: A generative pre-trained transformer model for openmp,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Ompgpt: A generative pre-trained transformer model for openmp,

Reference 11

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:01.198032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:01.198032Z digest=sha256:d7ecc53150621d1b009c1e1c25d55b30559749c6f8ee6b703d9eb5e3b01c3074

Observation 3ff618e3-b0f5-45e6-b2b1-516181de7d6b · outbound

This paper cites Can large language models write parallel code?.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Can large language models write parallel code?

Reference 12

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:01.288985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:01.288985Z digest=sha256:c4bc5c5ac77b7291eb483384a8562d1ad557df5eeced4e40a3930c79db485b2e

Observation d4119220-29b2-41bf-bdf3-682f4ff5514f · outbound

This paper cites Pcebench: A multi-dimensional benchmark for evaluating large language models in parallel code generation,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Pcebench: A multi-dimensional benchmark for evaluating large language models in parallel code generation,

Reference 13

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:01.389145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:01.389145Z digest=sha256:d1f8326f30033df8c8346d362632c698fe756d4d2f79af1ea8e6f316b26231c4

Observation 7e4bcb40-56ac-48e1-963d-1175a6dca1f6 · outbound

This paper cites Llm & hpc: Benchmarking deepseek’s performance in high-performance computing tasks,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Llm & hpc: Benchmarking deepseek’s performance in high-performance computing tasks,

Reference 14

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:01.517821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:01.517821Z digest=sha256:0f77cc84242eb05752078cf7d6f989cc444139cf15743fd67cc7cd4d74228a0c

Observation 5bb1689b-256d-4679-afaf-fbb5394ce897 · outbound

This paper cites Using chatgpt for converting sequential python programs into parallel code,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Using chatgpt for converting sequential python programs into parallel code,

Reference 15

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:01.618110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:01.618110Z digest=sha256:d69f783a5ff54b49c46efe2d2873b66154446f0785cb2982ec83a20f2b7c9769

Observation 288798ed-5cb0-4f89-9ddb-56f16fa76471 · outbound

This paper cites Kernelbench: Can llms write efficient gpu kernels?.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Kernelbench: Can llms write efficient gpu kernels?

Reference 16

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:01.706349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:01.706349Z digest=sha256:e30d4e0ceea4d2b351629df90bac299b2d4060425b68f9db1f7ce13e390b6a84

Observation 4eb8d5f3-3f40-43f0-ab46-2ba2d9abfea9 · outbound

This paper cites Fine-tuning gpt-5 for gpu kernel generation,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Fine-tuning gpt-5 for gpu kernel generation,

Reference 17

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:01.870813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:01.870813Z digest=sha256:9c2e99ad7b3b8679fdb6226acbb6627774b53ec846566132aa2fb67aab013aa8

Observation 251155f8-5976-4437-94a8-877fccd3444d · outbound

This paper cites Peak: A performance engineering ai-assistant for gpu kernels powered by natural language transformations,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Peak: A performance engineering ai-assistant for gpu kernels powered by natural language transformations,

Reference 18

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:01.939417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:01.939417Z digest=sha256:4eba4437b736ae4f05f458c9ee21630f9112c8b44e14c611889f0a8d873248d3

Observation 15f7100d-ef4d-4056-9eb2-cd6e6fc1b5c7 · outbound

This paper cites KernelBench: Can LLMs Write Efficient GPU Kernels?.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms KernelBench: Can LLMs Write Efficient GPU Kernels?

Reference 19

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:01.770814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:01.770814Z digest=sha256:9c03f6635177446915d15fc3d298c89270a888464cee5fe1acf1c97c8b0ab5d0

Observation a12b27ee-1fdc-42dc-8a23-e0c37cb0f012 · outbound

This paper cites Kernelfoundry: Hardware-aware evolutionary gpu kernel optimization,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Kernelfoundry: Hardware-aware evolutionary gpu kernel optimization,

Reference 20

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:02.069060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:02.069060Z digest=sha256:6fa52e074d16664a8feff1586e840bf242ac6a8f0c7fcdf40d0f87a3e4812f25

Observation 3eee525e-1711-4454-a2aa-e11428075fab · outbound

This paper cites Comparing llama-2 and gpt-3 llms for hpc kernels generation,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Comparing llama-2 and gpt-3 llms for hpc kernels generation,

Reference 21

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:02.187784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:02.187784Z digest=sha256:4125ad9f0368e5e384e1487e14574af6b53bbdb88f329c0ad870edbf5d83b119

Observation e41b4414-79c7-4edc-a541-bdbbb3a3475a · outbound

This paper cites Autokernel: Autonomous gpu kernel optimization via iterative agent-driven search,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Autokernel: Autonomous gpu kernel optimization via iterative agent-driven search,

Reference 22

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:02.025567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:02.025567Z digest=sha256:87c16a1cbf9b82387765f7fbc178afb969ea9340573db406904ae44ed8e0b899

Observation fd1f0be1-2509-4cfe-8273-acfce8b8466f · outbound

This paper cites HintPilot: LLM-based Compiler Hint Synthesis for Code Optimization.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms HintPilot: LLM-based Compiler Hint Synthesis for Code Optimization

Reference 23

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:02.347851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:02.347851Z digest=sha256:6b0a6490ebf3f3acf04084f3353d39c1da726c80ffbafca1ad642bf81e6fd5bd

Observation f41fc838-bdec-41f6-8a0e-67b7cd724500 · outbound

This paper cites Should ai optimize your code? a comparative study of current large language models versus classical optimizing compilers.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Should ai optimize your code? a comparative study of current large language models versus classical optimizing compilers

Reference 24

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:02.418219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:02.418219Z digest=sha256:7eb1039b3270636cc180b3fc6d4349281f49bdad65fd96e5413a899f7073831e

Observation c9376630-4ec0-40ae-8966-6b28092f0458 · outbound

This paper cites Performance-aligned llms for generating fast hpc code,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Performance-aligned llms for generating fast hpc code,

Reference 25

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:02.246772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:02.246772Z digest=sha256:60fefc531d8ab6b596398fa51e5f1692e6eb3a16ea3915e0287edf9d12686673

Observation 5df3d686-da5c-4770-9566-5d3dd1ba6d32 · outbound

This paper cites Evaluating ai-generated code for c++, fortran, go, java, julia, matlab, python, r, and rust,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Evaluating ai-generated code for c++, fortran, go, java, julia, matlab, python, r, and rust,

Reference 26

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:02.543023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:02.543023Z digest=sha256:d2b2e38bc0bba382ffb25c5020563813ca027f3ccd9ce3981c47dd92f1e0588c

Observation e1798f1c-6a9c-46e4-ae61-0caf53b29e1a · outbound

This paper cites The CLRS-Text Algorithmic Reasoning Language Benchmark.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms The CLRS-Text Algorithmic Reasoning Language Benchmark

Reference 27

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:02.603897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:02.603897Z digest=sha256:f6f2738a3173f9fd1480be8178826f4f71b55b036882981593214300db152c93

Observation 62387a01-e9cc-4112-9936-2d8083e80819 · outbound

This paper cites Do Large Language Models Understand Performance Optimization?.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Do Large Language Models Understand Performance Optimization?

Reference 28

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:02.450913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:02.450913Z digest=sha256:c473db7bd3822735d37c47cb79334863bfdba5e542653e4024a4f03d3ca730b8

Observation 27031af7-547f-4081-a226-602584a6d707 · outbound

This paper cites LASSI: An LLM-based automated self-correcting pipeline for translating parallel scientific codes.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms LASSI: An LLM-based automated self-correcting pipeline for translating parallel scientific codes

Reference 29

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:02.748058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:02.748058Z digest=sha256:5091998ea5decbddb79710654b2119c20de54ed8f32c00b0ad2a4c2b9c3dc3d4

Observation ed31d419-8e1e-4b2a-abd7-c52f4fe129f7 · outbound

This paper cites Parallel code generation with large language model,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Parallel code generation with large language model,

Reference 30

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:02.799819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:02.799819Z digest=sha256:7fd0f6ff989649d85536f93d0f61e8456dbf82043c6292805eae09fcef148a5a

Observation 1aba133a-9669-4b18-8ef1-6913262e4d0a · outbound

This paper cites Cursor: The AI code editor,.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Cursor: The AI code editor,

Reference 31

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:02.654623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:02.654623Z digest=sha256:151038a6acf31940284dba123f1e861426917eeca5bf5ab3c150bf70629e3405

Observation 6ee64eae-394e-4d51-8c1d-a886880ee99c · outbound

This paper cites Can Large Language Models Write Parallel Code?.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Can Large Language Models Write Parallel Code?

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:01.314848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:01.314848Z digest=sha256:ebfc616ed091368fb29ad49315f34fdf530bc066d92d61c1a9757059e1ba9d93

Observation 3d5904d1-881c-4cb4-b0e2-1835ec3192b7 · outbound

This paper cites Available: https://arxiv.org/abs/2508.11126.

Cross-Model Cross-Language AI Coding Agent Performance: Accuracy and Speed of Parallel CLRS Algorithms Available: https://arxiv.org/abs/2508.11126

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-07-30T11:33:00.409266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T11:33:00.409266Z digest=sha256:cc07aba050ef3c6376a94fba5e4dfd555aa6c11692366fbb4f5be60fdfe00e3e

Pith citing papers

No inbound Pith citation observations are available.