Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:03:31.767777Z
Paper Citation Record · LEDGER
Evaluating and Improving Large Language Models for Competitive Program Generation
As of 20 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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-12T02:46:48.375901Z
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:27.605289Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:03:36.422759Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- verified exact
- raw_fallback, observed 2026-08-06T22:03:33.030785Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- verified exact
- 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 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:27.978908Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- verified exact
- 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 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:28.145297Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:28.258022Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:28.369986Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:28.444681Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:28.588695Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:28.728894Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:28.782849Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:28.866165Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:28.988906Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T22:03:36.117423Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T22:03:35.823752Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T22:03:35.485962Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T22:03:35.160210Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:29.547120Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T22:03:34.947212Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:03:34.706339Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T22:03:34.560079Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:30.119619Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:03:34.293637Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:03:34.142805Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:30.526162Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:30.637102Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- verified fuzzy
- 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 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- verified fuzzy
- 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 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:31.047261Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T22:03:33.548955Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- verified fuzzy
- 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 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:31.461496Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- verified exact
- 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 2026-08-19T06:32:44.657259+00:00.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:03:31.682090Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- verified fuzzy
- 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 2026-08-19T06:32:44.657259+00:00.
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 2026-08-19T06:32:44.657259+00:00.