Paper Citation Record · LEDGER

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

As of 14 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 18 inbound Pith citation observations for arXiv:2505.21297.

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

pith.paper-citation-record.v1
2505.21297 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:40:20.293962Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:39:56.905741Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

39 of 39 outbound references displayed

verified exact0
verified fuzzy12
unresolved25
parse uncertain1
malformed identifier1
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation fcc68b24-1561-4ac4-b07e-7b6a1fe0f0d2 · outbound

This paper cites Phi-4-reasoning Technical Report.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Phi-4-reasoning Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:16.083583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b654619-c3fc-4ca8-a09e-152c3eac864c · outbound

This paper cites OpenCodeReasoning: Advancing Data Distillation for Competitive Coding.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset OpenCodeReasoning: Advancing Data Distillation for Competitive Coding

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:16.181554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26338d3b-3d9e-4ec8-b43e-38129ae7965f · outbound

This paper cites Program synthesis with large language models, 2021.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Program synthesis with large language models, 2021

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:16.273875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40eb8e2b-d5c5-46a3-8548-6d6af9ba9737 · outbound

This paper cites Code alpaca: An instruction-following llama model for code generation.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Code alpaca: An instruction-following llama model for code generation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:40:23.075969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation dcc02d33-6bc9-463e-acc3-d2bf5cd08cc4 · outbound

This paper cites CodeT: Code Generation with Generated Tests.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset CodeT: Code Generation with Generated Tests

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:16.588843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3f36bcf-01a8-458c-a4f2-f92f3253823f · outbound

This paper cites an unresolved cited work.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:40:22.954751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 01e5abcf-7b53-4efd-a508-64168cc282e1 · outbound

This paper cites FlashAttention-2: Faster attention with better parallelism and work partitioning.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset FlashAttention-2: Faster attention with better parallelism and work partitioning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:16.780708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6db72fc4-c218-4d06-a80d-91872720b3d0 · outbound

This paper cites rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:16.872558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20a40a32-c38a-4936-8984-0894f7044d2f · outbound

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

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:16.962324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 461327ea-3794-4e9d-882a-15b77eef2ef7 · outbound

This paper cites Measuring Coding Challenge Competence With APPS.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Measuring Coding Challenge Competence With APPS

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:17.007441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6861a483-2a64-4ca9-8b22-1281f01a01ca · outbound

This paper cites Enhancing Large Language Models in Coding Through Multi-Perspective Self-Consistency.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Enhancing Large Language Models in Coding Through Multi-Perspective Self-Consistency

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:17.057331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 896ecf03-ea14-42c8-8b3a-b53fe11ec73a · outbound

This paper cites OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:17.124812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 056d6f3b-8055-457c-9cb0-12be14510874 · outbound

This paper cites Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:17.228117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b10d1232-dd91-4e6b-9ede-17f4cd5bdf76 · outbound

This paper cites Codeforces-python-submissions.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Codeforces-python-submissions

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:40:22.793850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3e0b267f-daae-4249-a568-39a2eee0b95d · outbound

This paper cites an unresolved cited work.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Unresolved cited work

Reference 15

Resolution: parse uncertain; raw_fallback, observed 2026-08-07T13:40:22.651138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c3526c4b-b142-40e9-bee4-0f7b54e4c4ae · outbound

This paper cites Qwen2.5-coder technical report.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Qwen2.5-coder technical report

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:40:22.523092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 702dc0d1-bde7-44e2-8e8c-342a683f50a7 · outbound

This paper cites OpenAI o1 System Card.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset OpenAI o1 System Card

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:17.594742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cbdfd91-9453-465a-b1eb-a1be50dc5810 · outbound

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

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:17.736001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92ad93bd-bd2c-4310-bc20-818a503a8e99 · outbound

This paper cites Numina- math.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Numina- math

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:40:22.348907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 007173f1-59ce-4784-b6c0-7b843d0f61b5 · outbound

This paper cites TACO: Topics in Algorithmic COde generation dataset.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset TACO: Topics in Algorithmic COde generation dataset

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:18.118291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ff21bb8-8a55-48bc-b5f8-4f18ac6188cd · outbound

This paper cites Competition-level code generation with alphacode.Science, 378(6624):1092–1097, 2022.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Competition-level code generation with alphacode.Science, 378(6624):1092–1097, 2022

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:18.298848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9308fc5-b406-4e2f-9416-619ac1e6e120 · outbound

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

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Is your code generated by chatGPT really correct? rigorous evaluation of large language models for code generation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:18.424956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fcb0264-1839-4981-b514-7fbe9dbf955a · outbound

This paper cites Wizardcoder: Empowering code large language models with evol-instruct.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Wizardcoder: Empowering code large language models with evol-instruct

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:40:22.201629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8532f7c9-5869-4ff1-8120-4cb818ed9824 · outbound

This paper cites Deepcoder: A fully open-source 14b coder at o3-mini level.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Deepcoder: A fully open-source 14b coder at o3-mini level

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:40:22.064746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f89a8fae-3a69-4044-9611-31b3326241fe · outbound

This paper cites Open r1: Update 3, 2025.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Open r1: Update 3, 2025

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:40:21.914808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9ad325d3-e2e5-4c7b-ac24-6edf60c79f32 · outbound

This paper cites Can Language Models Solve Olympiad Programming?.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Can Language Models Solve Olympiad Programming?

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:18.998678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd4deb0c-1f62-43f8-af82-e8cd72a7e110 · outbound

This paper cites Open Thoughts.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Open Thoughts

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:19.131494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff6195a5-ff97-4e90-908c-01f13b277e54 · outbound

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

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Qwq-32b: Embracing the power of reinforcement learning, March 2025

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:19.251139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f66b985-88b3-44d3-b80d-af466b89e55f · outbound

This paper cites Magicoder: Empow- ering code generation with OSS-instruct.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Magicoder: Empow- ering code generation with OSS-instruct

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:19.364811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35958b2c-b5fa-4e7f-97b5-9387ec3b2d82 · outbound

This paper cites Kodcode: A diverse, challenging, and verifiable synthetic dataset for coding, 2025.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Kodcode: A diverse, challenging, and verifiable synthetic dataset for coding, 2025

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:19.464965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7894063-4fc4-4b2e-b2aa-3fd15f9e84d3 · outbound

This paper cites Wavecoder: Widespread and versatile enhancement for code large language models by instruction tuning.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Wavecoder: Widespread and versatile enhancement for code large language models by instruction tuning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:19.574831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d1bf505-893d-4b47-a5fc-ddfbb1fe33c0 · outbound

This paper cites ACECODER: Acing Coder RL via Automated Test-Case Synthesis.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset ACECODER: Acing Coder RL via Automated Test-Case Synthesis

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:19.680813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1b05727-e8e1-4fe2-b92d-80136fc2c488 · outbound

This paper cites Algo: Synthe- sizing algorithmic programs with generated oracle verifiers.Advances in Neural Information Processing Systems, 36:54769–54784, 2023.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Algo: Synthe- sizing algorithmic programs with generated oracle verifiers.Advances in Neural Information Processing Systems, 36:54769–54784, 2023

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:40:21.707926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8fa0b0cb-40ff-44f7-9096-c22dd012a6ec · outbound

This paper cites SRPO: A Cross-Domain Implementation of Large-Scale Reinforcement Learning on LLM.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset SRPO: A Cross-Domain Implementation of Large-Scale Reinforcement Learning on LLM

Reference 35

Resolution: malformed identifier; no resolver link, observed 2026-08-07T13:40:19.810322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13034de7-14a4-4813-8a2f-db51802bd916 · outbound

This paper cites Identify the reasoning steps (e.g., Step 1, Step 2, Step 3) and summarize the knowledge points tested in the original problem.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Identify the reasoning steps (e.g., Step 1, Step 2, Step 3) and summarize the knowledge points tested in the original problem

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:40:21.537304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 628d8401-4412-4de9-9c83-94ec70d3fc7e · outbound

This paper cites as in the original problem.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset as in the original problem

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:40:21.360221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f5f6c11a-9489-41d1-a965-91c29498e444 · outbound

This paper cites an unresolved cited work.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset Unresolved cited work

Reference 38

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:40:21.226217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9cb65650-01cc-4db2-8f4a-8f56e56e1029 · outbound

This paper cites The function should validate that the parameters fall within the specified constraints.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset The function should validate that the parameters fall within the specified constraints

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:40:20.994739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 289d4c91-d9c0-4372-b27f-ae1bddb59ffc · outbound

This paper cites t e s t _ i n p u t s.

rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset t e s t _ i n p u t s

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:40:20.766559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

Observation 4fe2febf-5736-49ce-ae1f-f9eefc4f3563 · inbound

HardTests: Synthesizing High-Quality Test Cases for LLM Coding cites this paper.

HardTests: Synthesizing High-Quality Test Cases for LLM Coding rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T12:39:56.905741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5737eabc-8cf1-4b86-ad60-e01076865642 · inbound

Xolver: Multi-Agent Reasoning with Holistic Experience Learning Just Like an Olympiad Team cites this paper.

Xolver: Multi-Agent Reasoning with Holistic Experience Learning Just Like an Olympiad Team rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T00:24:14.823958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4783c4d-9b91-40d1-b317-424793164e81 · inbound

Efficiency of turbulence cites this paper.

Efficiency of turbulence rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T00:58:28.854908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 704f9051-ab95-404c-92f1-ef3064d75831 · inbound

Hermes 4 Technical Report cites this paper.

Hermes 4 Technical Report rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-05T16:32:54.565609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c76a4272-a573-4d42-b4c2-841bcc948115 · inbound

Generating Verifiable Chain of Thoughts from Exection-Traces cites this paper.

Generating Verifiable Chain of Thoughts from Exection-Traces rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:19:04.874552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3b969afe-a100-4c04-a8c7-9aa829807994 · inbound

Toward Training Superintelligent Software Agents through Self-Play SWE-RL cites this paper.

Toward Training Superintelligent Software Agents through Self-Play SWE-RL rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-21T16:10:20.304045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a1596c99-53ba-4181-8721-18c2a9ed6bb6 · inbound

Toward Training Superintelligent Software Agents through Self-Play SWE-RL cites this paper.

Toward Training Superintelligent Software Agents through Self-Play SWE-RL rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T15:02:12.542382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22512446-27c3-4a5f-b5ba-4a950ea1026b · inbound

Embarrassingly Simple Self-Distillation Improves Code Generation cites this paper.

Embarrassingly Simple Self-Distillation Improves Code Generation rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-13T14:33:35.834383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96f2c97f-4264-4fa9-88ac-eb272e781965 · inbound

GrandCode: Achieving Grandmaster Level in Competitive Programming via Agentic Reinforcement Learning cites this paper.

GrandCode: Achieving Grandmaster Level in Competitive Programming via Agentic Reinforcement Learning rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:33:16.592695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0bd7f13a-1df7-42bc-a8ed-2af1a25489b0 · inbound

You Don't Need Public Tests to Generate Correct Code cites this paper.

You Don't Need Public Tests to Generate Correct Code rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-09T20:58:06.456959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2d08fc99-79e2-4780-b589-6841fcddfe49 · inbound

PaT: Planning-after-Trial for Efficient Test-Time Code Generation cites this paper.

PaT: Planning-after-Trial for Efficient Test-Time Code Generation rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T02:45:59.015551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b5cd3b4d-275f-4a7a-bbc8-507aa9f4925a · inbound

Primal Generation, Dual Judgment: Self-Training from Test-Time Scaling cites this paper.

Primal Generation, Dual Judgment: Self-Training from Test-Time Scaling rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-13T02:27:07.007259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e9ff6463-e654-470b-8983-92d96f4f0f0f · inbound

Primal Generation, Dual Judgment: Self-Training from Test-Time Scaling cites this paper.

Primal Generation, Dual Judgment: Self-Training from Test-Time Scaling rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:47:58.045025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bceb5667-4686-4c9d-bc69-7f142d9461ad · inbound

Attention Amnesia in Hybrid LLMs: When CoT Fine-Tuning Breaks Long-Range Recall, and How to Fix It cites this paper.

Attention Amnesia in Hybrid LLMs: When CoT Fine-Tuning Breaks Long-Range Recall, and How to Fix It rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-06-27T13:10:55.902231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6a2d1e07-d050-4cc4-a8be-f141e3950cc7 · inbound

From Trainee to Trainer: LLM-Designed Training Environment for RL with Multi-Agent Reasoning cites this paper.

From Trainee to Trainer: LLM-Designed Training Environment for RL with Multi-Agent Reasoning rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-06-27T01:00:19.836473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b8b7c27f-5878-44bc-a3f6-d2ab35964a23 · inbound

The Generalization Spectrum: A Chromatographic Approach to Evaluating Learning Algorithms cites this paper.

The Generalization Spectrum: A Chromatographic Approach to Evaluating Learning Algorithms rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-07-04T20:00:08.054031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bd2963ac-e7f9-48ac-87c3-d0e5e4c56045 · inbound

The Generalization Spectrum: A Chromatographic Approach to Evaluating Learning Algorithms cites this paper.

The Generalization Spectrum: A Chromatographic Approach to Evaluating Learning Algorithms rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-07-04T13:09:50.545490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9b77a0bf-18db-4068-aff5-9f5d4053c4b0 · inbound

Reinforcement Learning without Ground-Truth Solutions can Improve LLMs cites this paper.

Reinforcement Learning without Ground-Truth Solutions can Improve LLMs rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T13:59:51.922229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.