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Paper Citation Record · LEDGER

Evaluating and Improving Large Language Models for Competitive Program Generation

As of 7 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 2026-08-06T06:34:29.942622+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=pdf_text observed=2026-08-06T22:03:27.605289Z digest=sha256:0002ac73ae6888a26bf031cc8bb7eab27a4676d46c28da25ae97826f9a8b32d2

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+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

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source=pdf_text observed=2026-08-06T22:03:27.978908Z digest=sha256:9c8089c97808e90927f06762e226c894ce1917239fb7f1658041097f7d9d09c1

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T22:03:28.048952Z digest=sha256:f4d667620845176f307db4f16fa9feb65256e1cfd896b1abd78bc29269b3f1df

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=sha256:45664717854ce9e58578098c8cb4155aa88f3055a8bcda14639c6cd144f5a45f

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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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:a4c736ddb027a4005e7999f26944ed8172b8348947cf8420c8e720d9fd6091ee

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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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:de5cf76abbced0bae887d40586b89e11c8763e39171f6a5c75762777e4d42d65

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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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:cceb194625974a14ca13f2fdfc08d41e975cf9b87c87c8dd07b61095167b348f

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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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:dcb4ef87b9c663d82b3665d87c0f61cbdb7cac490eb14694a4c35b53de7769b3

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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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+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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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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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Observation 5f5d06e0-8b2e-4a49-aff7-a1bdf70eaca8 · outbound

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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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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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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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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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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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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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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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+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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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+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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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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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+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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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

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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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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source=pdf_text observed=2026-08-06T22:03:31.682090Z digest=sha256:2a8ef01b857f4624b5edc7e1677a5e3f3257830649915747d7e4a0d643934adb

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T22:03:31.767777Z digest=sha256:04006cd06c6a07201474fe677c833f546112f17753c7705db54667d7cf458eb4

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

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:31:24.620351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-05-12T02:46:48.375901Z digest=sha256:4c2924be88d4921cadb8eb7bae0c448348b1e793f2aa2869944aa789ad0936c7