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Paper Citation Record · LEDGER

Evaluating and Improving Large Language Models for Competitive Program Generation

As of 9 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2506.22954.

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

pith.paper-citation-record.v1
2506.22954 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:03:31.767777Z

measured 38 of 38 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T02:46:48.375901Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T07:31:24.613360Z

Reference resolution

37 of 37 outbound references displayed

  • verified exact4
  • verified fuzzy8
  • unresolved25
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 16483639-9544-4f4b-9981-ae097699865a · outbound

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

Evaluating and Improving Large Language Models for Competitive Program Generation A Survey on Large Language Models for Code Generation

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:03:27.605289Z digest=sha256:29fd5e46db71bd2d99c0e5013cdfaeccfc19dd64ed0f0c54a4eec541e2e27583

Observation efdfa3b4-7141-4dbc-9bba-53ebd5bbf5ed · outbound

This paper cites Zhang, D.

Evaluating and Improving Large Language Models for Competitive Program Generation Zhang, D

Reference 2

Resolution
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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.

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Observation fdc3f478-a7c2-4682-868e-2bf435ef5797 · outbound

This paper cites an unresolved cited work.

Evaluating and Improving Large Language Models for Competitive Program Generation Unresolved cited work

Reference 3

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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.

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Observation ae1a0d4a-54e6-45b3-8e5e-a32e53d9f1d2 · outbound

This paper cites Radiation resistance of fine-grained ceramics Y2.5Nd0.5Al5O12 under Xe-ions irradiation.

Evaluating and Improving Large Language Models for Competitive Program Generation Radiation resistance of fine-grained ceramics Y2.5Nd0.5Al5O12 under Xe-ions irradiation

Reference 4

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local_arxiv, observed 2026-08-06T22:03:32.777658Z

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.

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Observation b595b00b-1e7c-4379-b156-23e734a806f1 · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Evaluating and Improving Large Language Models for Competitive Program Generation Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:03:27.978908Z digest=sha256:e5c7df12a660e71aa133da6e590707f4e2457b95090f250454b99cd05947bcc5

Observation 8cf030b4-3b19-465c-8308-7032314ca97c · outbound

This paper cites Enhancing Computer Programming Education with LLMs: A Study on Effective Prompt Engineering for Python Code Generation.

Evaluating and Improving Large Language Models for Competitive Program Generation Enhancing Computer Programming Education with LLMs: A Study on Effective Prompt Engineering for Python Code Generation

Reference 6

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local_arxiv, observed 2026-08-06T22:03:32.550494Z

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.

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Observation 90d533eb-7280-4fce-b3c0-2a1c8656c320 · outbound

This paper cites Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering.

Evaluating and Improving Large Language Models for Competitive Program Generation Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering

Reference 7

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source=pdf_text observed=2026-08-06T22:03:28.145297Z digest=sha256:ce7315e85195dcc4215373b07cbb4acc7baa0bbf7cf5b5c64bc79c24d6c54926

Observation 1cf4f9c5-8f35-4285-a471-cbbdada59348 · outbound

This paper cites VeriContaminated: Assessing LLM-Driven Verilog Coding for Data Contamination.

Evaluating and Improving Large Language Models for Competitive Program Generation VeriContaminated: Assessing LLM-Driven Verilog Coding for Data Contamination

Reference 8

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source=pdf_text observed=2026-08-06T22:03:28.258022Z digest=sha256:48eb48db163013f3157ca9a88c921dc0d000de44c17ba8ffc011f7a0bad19b88

Observation 515d0685-b149-4a0f-a75b-7d8e1e6cfc92 · outbound

This paper cites On Leakage of Code Generation Evaluation Datasets.

Evaluating and Improving Large Language Models for Competitive Program Generation On Leakage of Code Generation Evaluation Datasets

Reference 9

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source=pdf_text observed=2026-08-06T22:03:28.369986Z digest=sha256:eb9fa4fc3ef5d4119acfb4562051ce99bc73dba730f246e0c1d84b618347cdbf

Observation 8d6351cf-a0c4-40a7-b93b-a007a1acc4d5 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Evaluating and Improving Large Language Models for Competitive Program Generation Evaluating Large Language Models Trained on Code

Reference 10

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source=pdf_text observed=2026-08-06T22:03:28.444681Z digest=sha256:57ddeba81a2f35d765a3c5633e3c4780b1ea877bd6a163ac40b5fc548b213c1f

Observation 319bcdc1-0403-4589-86ef-0aed2b9570a2 · outbound

This paper cites Program Synthesis with Large Language Models.

Evaluating and Improving Large Language Models for Competitive Program Generation Program Synthesis with Large Language Models

Reference 11

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source=pdf_text observed=2026-08-06T22:03:28.588695Z digest=sha256:7523feb9dd541ddff03bfcfd17afec5c7b89fe35b115101d0c3cf04d3b6541ad

Observation f1bda1d8-c08a-4c9a-8336-4ee241f96f24 · outbound

This paper cites Quantifying Contamination in Evaluating Code Generation Capabilities of Language Models.

Evaluating and Improving Large Language Models for Competitive Program Generation Quantifying Contamination in Evaluating Code Generation Capabilities of Language Models

Reference 12

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:03:28.728894Z digest=sha256:906470555419ec2cda84d53083baad54fef973eb42f96ae89f2c552dd55d1408

Observation 380c017e-2dc7-48cc-a404-6453a238f449 · outbound

This paper cites Competition-Level Problems are Effective LLM Evaluators.

Evaluating and Improving Large Language Models for Competitive Program Generation Competition-Level Problems are Effective LLM Evaluators

Reference 13

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source=pdf_text observed=2026-08-06T22:03:28.782849Z digest=sha256:d5cab739c63400e782041a85ca443cc70a584d7df2a5ac925378339b42279231

Observation c7195200-d475-4c66-a2ce-d0b42a41c470 · outbound

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

Evaluating and Improving Large Language Models for Competitive Program Generation LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming?

Reference 14

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source=pdf_text observed=2026-08-06T22:03:28.866165Z digest=sha256:18bf6e21f4ff7c494c638b01fcaf93c6ba5d585fc6f869b494d8324da518c337

Observation 288f6c1a-8c97-48c2-936a-db0663188c1b · outbound

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

Evaluating and Improving Large Language Models for Competitive Program Generation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 15

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source=pdf_text observed=2026-08-06T22:03:28.988906Z digest=sha256:2412a46466406898e45019c7a5e1eeb66d1ee5d63e579a7a3551d477c439ac79

Observation e304bd05-2203-479f-b069-3e5d6a155d76 · outbound

This paper cites an unresolved cited work.

Evaluating and Improving Large Language Models for Competitive Program Generation Unresolved cited work

Reference 16

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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.

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Observation f82abb75-51da-4f34-9422-d5c15575db51 · outbound

This paper cites an unresolved cited work.

Evaluating and Improving Large Language Models for Competitive Program Generation Unresolved cited work

Reference 17

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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.

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Observation 0486e9e2-5b88-478c-aa45-316cfa2ed790 · outbound

This paper cites an unresolved cited work.

Evaluating and Improving Large Language Models for Competitive Program Generation Unresolved cited work

Reference 18

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

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Observation 3eed8bb0-d5a5-4f0e-86a5-b0f4f3f1bef7 · outbound

This paper cites an unresolved cited work.

Evaluating and Improving Large Language Models for Competitive Program Generation Unresolved cited work

Reference 19

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

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Observation 5f5d06e0-8b2e-4a49-aff7-a1bdf70eaca8 · outbound

This paper cites an unresolved cited work.

Evaluating and Improving Large Language Models for Competitive Program Generation Unresolved cited work

Reference 20

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Observation ba888748-7538-456b-9210-391114bf6af1 · outbound

This paper cites an unresolved cited work.

Evaluating and Improving Large Language Models for Competitive Program Generation Unresolved cited work

Reference 21

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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.

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Observation 0f988cf3-13d1-4bc6-a614-db07270f1898 · outbound

This paper cites Cohen, A coe fficient of agreement for nominal scales, Educational and psychological measurement 20 (1) (1960) 37–46.

Evaluating and Improving Large Language Models for Competitive Program Generation Cohen, A coe fficient of agreement for nominal scales, Educational and psychological measurement 20 (1) (1960) 37–46

Reference 22

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

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Observation 31f9da85-90f3-4e04-b8c2-44933fb5b01e · outbound

This paper cites an unresolved cited work.

Evaluating and Improving Large Language Models for Competitive Program Generation Unresolved cited work

Reference 23

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

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Observation 69c8285d-e73b-4b2b-835e-57883eacaaec · outbound

This paper cites Lost in the Middle: How Language Models Use Long Contexts.

Evaluating and Improving Large Language Models for Competitive Program Generation Lost in the Middle: How Language Models Use Long Contexts

Reference 24

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Observation 759d5ec7-e613-4f2a-9855-123bb3f7aa87 · outbound

This paper cites Reynolds, K.

Evaluating and Improving Large Language Models for Competitive Program Generation Reynolds, K

Reference 25

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

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Observation 2b1b5d28-f9cd-45d2-91db-dfbaa8db2294 · outbound

This paper cites Beurer-Kellner, M.

Evaluating and Improving Large Language Models for Competitive Program Generation Beurer-Kellner, M

Reference 26

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

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Observation 68dec1d7-e9d3-4631-b487-2ffd602b4a66 · outbound

This paper cites Unleashing the potential of prompt engineering for large language models.

Evaluating and Improving Large Language Models for Competitive Program Generation Unleashing the potential of prompt engineering for large language models

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 592386d8-cadf-4471-b632-729753b65e9d · outbound

This paper cites ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection.

Evaluating and Improving Large Language Models for Competitive Program Generation ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection

Reference 28

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source=pdf_text observed=2026-08-06T22:03:30.637102Z digest=sha256:8c27b52cd32034472d7280e8146112a9c7e2d2912aacea1310df53d0fadd9911

Observation 068adf23-5a51-4f7d-95cc-182d6c750f9a · outbound

This paper cites Zhang, K.

Evaluating and Improving Large Language Models for Competitive Program Generation Zhang, K

Reference 29

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raw_fallback, observed 2026-08-06T22:03:33.949398Z

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.

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Observation baea3e6b-7929-4e97-9e72-5869ce90472d · outbound

This paper cites Shakya, F.

Evaluating and Improving Large Language Models for Competitive Program Generation Shakya, F

Reference 30

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raw_fallback, observed 2026-08-06T22:03:33.692238Z

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.

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Observation 11c5d73a-cfc3-4ae7-a56c-dd45ab27d8f9 · outbound

This paper cites Measuring Coding Challenge Competence With APPS.

Evaluating and Improving Large Language Models for Competitive Program Generation Measuring Coding Challenge Competence With APPS

Reference 31

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source=pdf_text observed=2026-08-06T22:03:31.047261Z digest=sha256:e965facfe905f99c1bacebd3287fd7e3b7cce3049b5cb9bdb3d3b9874af4c433

Observation 6b485b04-a144-4a6c-b362-bf82e88113e7 · outbound

This paper cites an unresolved cited work.

Evaluating and Improving Large Language Models for Competitive Program Generation Unresolved cited work

Reference 32

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raw_fallback, observed 2026-08-06T22:03:33.548955Z

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

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Observation 359ca614-676a-4ed1-aa48-f37f39cd85e6 · outbound

This paper cites Zhang, Z.

Evaluating and Improving Large Language Models for Competitive Program Generation Zhang, Z

Reference 33

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raw_fallback, observed 2026-08-06T22:03:33.386799Z

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.

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Observation 1152e4b5-1248-475f-a60c-9148f51b7c78 · outbound

This paper cites MapCoder: Multi-Agent Code Generation for Competitive Problem Solving.

Evaluating and Improving Large Language Models for Competitive Program Generation MapCoder: Multi-Agent Code Generation for Competitive Problem Solving

Reference 34

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source=pdf_text observed=2026-08-06T22:03:31.461496Z digest=sha256:efe29b65775fb3738be78ac1f8a43ebfa478b39ef2c9483f99911edfa5b55c67

Observation 083e112b-a6a8-458d-b186-2332c293b30c · outbound

This paper cites Souza, R.

Evaluating and Improving Large Language Models for Competitive Program Generation Souza, R

Reference 35

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raw_fallback, observed 2026-08-06T22:03:32.078947Z

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=2026-08-06T22:03:31.582802Z digest=sha256:56c58c57a701ba1fce8e882156dad508e0dc756b4181deeb1f9c6f369a7aa159

Observation 427a19f3-d228-419f-9323-740974b83fa5 · outbound

This paper cites ProBench: Benchmarking Large Language Models in Competitive Programming.

Evaluating and Improving Large Language Models for Competitive Program Generation ProBench: Benchmarking Large Language Models in Competitive Programming

Reference 36

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:03:31.682090Z digest=sha256:8305e38246e32405305855a4cdf4500b4892ba08dc6d7050572b5ca740528bd5

Observation f4f41a1a-9047-4609-b371-5b3b1ff5edab · outbound

This paper cites More information can be found at: https://xchencs.github.io/index.html.

Evaluating and Improving Large Language Models for Competitive Program Generation More information can be found at: https://xchencs.github.io/index.html

Reference 2023

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raw_fallback, observed 2026-08-06T22:03:33.211048Z

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=2026-08-06T22:03:31.767777Z digest=sha256:eb47c345a7767a1023ab258540b3adeebedc38453e40536848693a6fec5eaae5

Pith citing papers

Observation a0e794a6-a7ce-436c-934f-dc95947900f7 · inbound

When Independent Sampling Outperforms Agentic Reasoning cites this paper.

When Independent Sampling Outperforms Agentic Reasoning Evaluating and Improving Large Language Models for Competitive Program Generation

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source=arxiv_source observed=2026-05-12T02:46:48.375901Z digest=sha256:48cd59bddc52a73e1c6db55678216957ce9b392c291e8395768cda50ad2b51b7