Paper Citation Record · LEDGER

Coding Triangle: How Does Large Language Model Understand Code?

As of 7 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:2507.06138.

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

pith.paper-citation-record.v1
2507.06138 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:15:34.295265Z

measured 31 of 31 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T21:24:12.395140Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

30 of 30 outbound references displayed

verified exact0
verified fuzzy5
unresolved25
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e3e51fff-5e6c-4793-bb70-a0b4cbcb0a2d · outbound

This paper cites GPT-4 Technical Report.

Coding Triangle: How Does Large Language Model Understand Code? GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:31.319491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a365a6b5-88c8-4b5a-a7a1-81fd4d62132e · outbound

This paper cites Claude 3.5 sonnet.

Coding Triangle: How Does Large Language Model Understand Code? Claude 3.5 sonnet

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:31.436473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7051434b-8b71-42c3-a9e3-c0d78fdc2a30 · outbound

This paper cites Program Synthesis with Large Language Models.

Coding Triangle: How Does Large Language Model Understand Code? Program Synthesis with Large Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:31.621357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 200e52b0-ecfa-4123-a40b-4cc0530f59fa · outbound

This paper cites Qwen Technical Report.

Coding Triangle: How Does Large Language Model Understand Code? Qwen Technical Report

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:31.728286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 471aa647-3f9b-4994-a28c-1f586afd3284 · outbound

This paper cites Language Models are Few-Shot Learners.

Coding Triangle: How Does Large Language Model Understand Code? Language Models are Few-Shot Learners

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:31.815397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39ed476d-e59e-4400-a5e9-5dad069ce0c9 · outbound

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

Coding Triangle: How Does Large Language Model Understand Code? MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:31.911884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26de09f2-00ec-4454-9a6b-9ca100201ebe · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Coding Triangle: How Does Large Language Model Understand Code? Evaluating Large Language Models Trained on Code

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:32.143756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7281edc-39fb-42be-b8b2-e3aa8e4a286a · outbound

This paper cites The Llama 3 Herd of Models.

Coding Triangle: How Does Large Language Model Understand Code? The Llama 3 Herd of Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:32.249516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd9e01b2-eeaf-47c1-9956-99dfd4999c7c · outbound

This paper cites Competitive Programming with Large Reasoning Models.

Coding Triangle: How Does Large Language Model Understand Code? Competitive Programming with Large Reasoning Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:32.356639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e169ced6-7268-4a0e-b071-dbb55c63f6ad · outbound

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

Coding Triangle: How Does Large Language Model Understand Code? DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:32.431989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65491e5d-6e7b-496d-837a-10ed59f3db6d · outbound

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

Coding Triangle: How Does Large Language Model Understand Code? CodeEditorBench: Evaluating Code Editing Capability of Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:32.548428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14c450c0-fb89-4b51-aaff-6725c9baa936 · outbound

This paper cites Qwen2.5-Coder Technical Report.

Coding Triangle: How Does Large Language Model Understand Code? Qwen2.5-Coder Technical Report

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:32.631060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d543bcfc-dac4-49c5-a324-20235bde79ce · outbound

This paper cites LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code.

Coding Triangle: How Does Large Language Model Understand Code? LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:32.745959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57a1cefe-8fd1-4eba-a512-449a6c70f477 · outbound

This paper cites Mistral 7B.

Coding Triangle: How Does Large Language Model Understand Code? Mistral 7B

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:32.843530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14fbf7cb-c045-44bc-9529-74febc25a52d · outbound

This paper cites Competition-level code generation with alphacode.

Coding Triangle: How Does Large Language Model Understand Code? Competition-level code generation with alphacode

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:15:35.488251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f5b4ceed-068e-43fb-ad23-bbc3f8c4f042 · outbound

This paper cites AutoKaggle: A Multi-Agent Framework for Autonomous Data Science Competitions.

Coding Triangle: How Does Large Language Model Understand Code? AutoKaggle: A Multi-Agent Framework for Autonomous Data Science Competitions

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:33.042830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6fb03e8d-592c-4cb9-9643-a985274ae765 · outbound

This paper cites DeepSeek-V3 Technical Report.

Coding Triangle: How Does Large Language Model Understand Code? DeepSeek-V3 Technical Report

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:33.137256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2561591-789e-43e9-a343-f42d62990a39 · outbound

This paper cites M2rc-Eval: Massively Multilingual Repository-level Code Completion Evaluation.

Coding Triangle: How Does Large Language Model Understand Code? M2rc-Eval: Massively Multilingual Repository-level Code Completion Evaluation

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:33.200565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77b16742-3f2e-4cea-9372-d4b72b152eaf · outbound

This paper cites Is your code generated by chatgpt really correct? rigorous evaluation of large language models for code generation.

Coding Triangle: How Does Large Language Model Understand Code? Is your code generated by chatgpt really correct? rigorous evaluation of large language models for code generation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:33.307508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99f418b3-2ec2-4216-9725-a200a3e024a6 · outbound

This paper cites StarCoder 2 and The Stack v2: The Next Generation.

Coding Triangle: How Does Large Language Model Understand Code? StarCoder 2 and The Stack v2: The Next Generation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:33.406137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e738d167-4ecc-4ae2-be30-a3cc6f371df4 · outbound

This paper cites an unresolved cited work.

Coding Triangle: How Does Large Language Model Understand Code? Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:15:35.345101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bf3523df-e592-4226-80aa-16766cfb9a80 · outbound

This paper cites Openai o1 system card.

Coding Triangle: How Does Large Language Model Understand Code? Openai o1 system card

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:15:35.175911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b9822e12-1061-42f4-8683-34ae7ed3c85f · outbound

This paper cites Openai o3 system card.

Coding Triangle: How Does Large Language Model Understand Code? Openai o3 system card

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:15:34.988614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b405da22-62ea-4c29-a8e2-1d761bf37992 · outbound

This paper cites Openai o3-mini system card.

Coding Triangle: How Does Large Language Model Understand Code? Openai o3-mini system card

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:15:34.779915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b39c2840-3101-40eb-8d0f-024255681f83 · outbound

This paper cites Qwen3: Think deeper, act faster.

Coding Triangle: How Does Large Language Model Understand Code? Qwen3: Think deeper, act faster

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:15:34.587917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e5c22150-9882-4b2f-b178-d07668600592 · outbound

This paper cites Qwq-32b: Embracing the power of reinforcement learning, March 2025.

Coding Triangle: How Does Large Language Model Understand Code? Qwq-32b: Embracing the power of reinforcement learning, March 2025

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:33.932515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c312a239-ee61-4022-b2b4-fd0568604c90 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Coding Triangle: How Does Large Language Model Understand Code? Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:34.024244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2ccf137-483a-4ee8-b322-8baa6c138f72 · outbound

This paper cites TableBench: A Comprehensive and Complex Benchmark for Table Question Answering.

Coding Triangle: How Does Large Language Model Understand Code? TableBench: A Comprehensive and Complex Benchmark for Table Question Answering

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:34.117604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80c0fd70-3fca-4867-ada7-7c57370a0c3e · outbound

This paper cites Qwen2 Technical Report.

Coding Triangle: How Does Large Language Model Understand Code? Qwen2 Technical Report

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:34.199084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ad0f66a-511a-4f42-97ad-8d774c609edb · outbound

This paper cites Qwen2.5 Technical Report.

Coding Triangle: How Does Large Language Model Understand Code? Qwen2.5 Technical Report

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:34.295265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 1ada2122-0e6d-4b38-8929-c3d1728ce4e9 · inbound

The Honest Quorum Problem: Epistemic Byzantine Fault Tolerance for Agentic Infrastructure cites this paper.

The Honest Quorum Problem: Epistemic Byzantine Fault Tolerance for Agentic Infrastructure Coding Triangle: How Does Large Language Model Understand Code?

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T21:24:12.395140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.