Paper Citation Record · LEDGER

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation

As of 8 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 1 inbound Pith citation observation for arXiv:2507.04697.

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

pith.paper-citation-record.v1
2507.04697 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:45:36.273850Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T13:38:48.308683Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T00:06:23.765366Z

Reference resolution

24 of 24 outbound references displayed

verified exact0
verified fuzzy9
unresolved13
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bacb8ff5-10c7-4c6e-989d-e5af50e52864 · outbound

This paper cites Attention is all you need,.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation Attention is all you need,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:45:37.171582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 92ad2ea9-ad10-43f4-9442-53cf88db1a9e · outbound

This paper cites GPT-4 Technical Report.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation GPT-4 Technical Report

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:36.139012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1caaff9d-ee45-4943-86e9-aa06d7f2425a · outbound

This paper cites Basic Linear Algebra Subprograms for Fortran Usage,.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation Basic Linear Algebra Subprograms for Fortran Usage,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:36.145316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76de9e30-0fc8-44df-87fa-5c4cbaffc5b5 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation Evaluating Large Language Models Trained on Code

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:36.150584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2abd5787-da15-4d0e-91f4-fa80976343d0 · outbound

This paper cites CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:36.161918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb64797a-4658-414d-ad36-46456a48547e · outbound

This paper cites StarCoder: may the source be with you!.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation StarCoder: may the source be with you!

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:36.169335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e49fe3c-1197-4576-81ab-dd21eced650e · outbound

This paper cites CodeRAG: Supportive Code Retrieval on Bigraph for Real-World Code Generation,.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation CodeRAG: Supportive Code Retrieval on Bigraph for Real-World Code Generation,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:36.175784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6c2c46d-6cad-4f59-bdef-bbffee62b570 · outbound

This paper cites LLM-Assisted Translation of Legacy FORTRAN Codes to C++: A Cross-Platform Study,.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation LLM-Assisted Translation of Legacy FORTRAN Codes to C++: A Cross-Platform Study,

Reference 8

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T19:45:37.154484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 606987da-c8be-4ce0-a9aa-fb89f55cbd2c · outbound

This paper cites Enhancing Code Translation in Language Models with Few-Shot Learning via Retrieval-Augmented Generation.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation Enhancing Code Translation in Language Models with Few-Shot Learning via Retrieval-Augmented Generation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:36.189596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92a36ca7-bcea-460f-b978-76f6ed237619 · outbound

This paper cites MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning,.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:45:37.132989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 334354b3-e99f-47e2-8137-749986085b87 · outbound

This paper cites HPC-GPT: Integrating Large Language Model for High-Performance Computing,.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation HPC-GPT: Integrating Large Language Model for High-Performance Computing,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:45:37.114366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c2f1115f-4415-4632-ad32-aa16b0440388 · outbound

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

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation HPC-Coder: Modeling Parallel Programs using Large Language Models,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:36.207180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b90191c-36f5-48c1-83ee-633171d9167c · outbound

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

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation Can Large Language Models Write Parallel Code?

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:45:37.095329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e6bddd72-e2b4-47da-836c-e7850db63dc4 · outbound

This paper cites LM4HPC: Towards Effective Language Model Ap- plication in High-Performance Computing,.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation LM4HPC: Towards Effective Language Model Ap- plication in High-Performance Computing,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:45:37.073792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1d17dadc-a590-40c6-be36-1376a431c90b · outbound

This paper cites MARCO: Multi-Agent Code Optimization with Real-Time Knowledge Integration for High-Performance Computing.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation MARCO: Multi-Agent Code Optimization with Real-Time Knowledge Integration for High-Performance Computing

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:36.223462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 064c75de-4a1d-40c0-9c12-c556681d0ce0 · outbound

This paper cites ARCS: Agentic Retrieval-Augmented Code Synthesis with Iterative Refine- ment,.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation ARCS: Agentic Retrieval-Augmented Code Synthesis with Iterative Refine- ment,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:36.228558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06e97a69-e0b0-4746-8d46-da5d3ed7e3bd · outbound

This paper cites MonoCoder: Domain-Specific Code Language Model for HPC Codes and Tasks.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation MonoCoder: Domain-Specific Code Language Model for HPC Codes and Tasks

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:36.233947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fd4827f-26e6-4196-83dc-d1e56e9769af · outbound

This paper cites QiMeng-GEMM: Automatically Generating High-Performance Matrix Multiplication Code by Exploiting Large Language Models,.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation QiMeng-GEMM: Automatically Generating High-Performance Matrix Multiplication Code by Exploiting Large Language Models,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:45:37.054723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 953c83b5-4c93-4275-a06d-8fc5a64d8152 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:36.243567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57ea575b-82af-4856-8166-512f5962be68 · outbound

This paper cites ChatBLAS: The First AI-Generated and Portable BLAS Library,.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation ChatBLAS: The First AI-Generated and Portable BLAS Library,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:45:37.035095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 31449328-a827-47d1-a62b-362069052c84 · outbound

This paper cites Comparing Llama-2 and GPT-3 LLMs for HPC kernels generation.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation Comparing Llama-2 and GPT-3 LLMs for HPC kernels generation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:36.253808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16f9facd-46ac-4066-b5f1-c285b0977ae1 · outbound

This paper cites Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation,.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:45:37.017276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 618fdfdd-ad3d-4cd4-b37d-56a04bfc24d6 · outbound

This paper cites BLAS++: C++ API for the Basic Linear Algebra Subroutines,.

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation BLAS++: C++ API for the Basic Linear Algebra Subroutines,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:45:36.998092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4704c71f-058d-44b8-a6ee-4ee40f0d277b · outbound

This paper cites Available: https://github.com/icl-utk-edu/blaspp/ TABLE 6: Performance of Level-3 routines (in GFlops/s, problem size: n = 2048).

Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation Available: https://github.com/icl-utk-edu/blaspp/ TABLE 6: Performance of Level-3 routines (in GFlops/s, problem size: n = 2048)

Reference 2023

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T19:45:36.977195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

Observation 87f681a0-4914-4202-9e02-6c417466d862 · inbound

CodegenBench: Can LLMs Write Efficient Code Across Architectures? cites this paper.

CodegenBench: Can LLMs Write Efficient Code Across Architectures? Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-02T00:06:23.768057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.