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Paper Citation Record · LEDGER

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation

As of 18 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2505.10594.

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

pith.paper-citation-record.v1
2505.10594 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:22:19.152777Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-08T17:37:51.790000Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T17:21:10.768449Z

Reference resolution

31 of 31 outbound references displayed

  • verified exact0
  • verified fuzzy4
  • unresolved27
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6f3767cd-7e28-49cb-9d27-0ae7d4320b8f · outbound

This paper cites DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.006242Z digest=sha256:51b0a724b4149486288bfd4f4f6180b2104f43dbf8493b41d27d55a976c8bb2c

Observation 344c348d-7791-4ddd-883d-324c3767f1c3 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 3

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no resolver link, observed 2026-08-15T21:22:19.010922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.010922Z digest=sha256:cd081255400e14dd83f01ddca48700e016cd796cb445c785a287daf0b3873c81

Observation 2ce294f3-647c-4e8f-9d44-6aae3aff4aa3 · outbound

This paper cites Tree of Thoughts: Deliberate Problem Solving with Large Language Models.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Reference 4

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no resolver link, observed 2026-08-15T21:22:19.015555Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.015555Z digest=sha256:f50d598dbb69c8133fbd53d84afc7f9ff0274bed249070f79891c885bb494756

Observation 0160462c-2e07-4431-9a9d-735280441106 · outbound

This paper cites AlphaMath Almost Zero: Process Supervision without Process.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation AlphaMath Almost Zero: Process Supervision without Process

Reference 5

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no resolver link, observed 2026-08-15T21:22:19.020587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.020587Z digest=sha256:e17e1f61860e7edde312c86abecb1ce74e7a20667cadde40999fc46bc64cceee

Observation 1e219a06-2a95-42f5-a6fe-d0d55e9030d0 · outbound

This paper cites LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical Reasoning.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical Reasoning

Reference 6

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no resolver link, observed 2026-08-15T21:22:19.025191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.025191Z digest=sha256:4c5f5acf576d7c2162eeebdfbcf7c247ad12ba78f8bb6fa46ad4ed2389181d56

Observation 437b3c6f-89cd-45ab-a0dc-8a5c7fca21eb · outbound

This paper cites WizardCoder: Empowering Code Large Language Models with Evol-Instruct.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation WizardCoder: Empowering Code Large Language Models with Evol-Instruct

Reference 7

Resolution
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no resolver link, observed 2026-08-15T21:22:19.030180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.030180Z digest=sha256:82e8426e59641554c931a84ca250c3e0928ae138b1a01b7fd942b0a8ba1a5e37

Observation aa550ed7-92f5-4c22-8f44-50bed3ee3925 · outbound

This paper cites WaveCoder: Widespread And Versatile Enhancement For Code Large Language Models By Instruction Tuning.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation WaveCoder: Widespread And Versatile Enhancement For Code Large Language Models By Instruction Tuning

Reference 8

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no resolver link, observed 2026-08-15T21:22:19.034292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.034292Z digest=sha256:4e289aca2787265dd5392e4559559a4c3fdecb4382875b0458e0d3546a2ec125

Observation 4a896f87-f4d6-48c1-8b0f-5ecb02873cd8 · outbound

This paper cites Magicoder: Empowering Code Generation with OSS-Instruct.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation Magicoder: Empowering Code Generation with OSS-Instruct

Reference 9

Resolution
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no resolver link, observed 2026-08-15T21:22:19.038663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.038663Z digest=sha256:c50176a6e69e57094ea249d79b7d68aa1a643be5e4dcfa4a8122cf6028a4d72f

Observation 44bd3ffe-f9ed-4004-ad79-63854f7f6591 · outbound

This paper cites StepCoder: Improve Code Generation with Reinforcement Learning from Compiler Feedback.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation StepCoder: Improve Code Generation with Reinforcement Learning from Compiler Feedback

Reference 10

Resolution
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no resolver link, observed 2026-08-15T21:22:19.042890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.042890Z digest=sha256:15c8e35c01d3ee109180cfcd54506b285a6d9766c6247ca656178b865277989f

Observation 5643fa06-d819-4d27-b1a1-861b482e74a8 · outbound

This paper cites Execution-based Code Generation using Deep Reinforcement Learning.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation Execution-based Code Generation using Deep Reinforcement Learning

Reference 11

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.047158Z digest=sha256:2daa3f87bdad30fd9fa497dd886d56cd9da36813c70cc2a39a65e3632528d4f4

Observation c5bb4075-ad1b-40fd-b894-284cdbc164f6 · outbound

This paper cites RLTF: Reinforcement Learning from Unit Test Feedback.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation RLTF: Reinforcement Learning from Unit Test Feedback

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.051890Z digest=sha256:d7ee4583cef7a98e5f13f9de9aa2c1ca4672663a327f499ddb78261ec16b79b5

Observation ce7385d9-2222-4810-9705-ac8a8d97df30 · outbound

This paper cites Qwen2.5-Coder Technical Report.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation Qwen2.5-Coder Technical Report

Reference 13

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.058568Z digest=sha256:1eda92fd124b9e25f981d5e403b529305b8567a7fa5a418ffe8ee4cc78ff91bb

Observation 51f43649-e44e-4600-bad7-db1d990ba2f3 · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 14

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.063467Z digest=sha256:30bb32f7462e33eebed801a76a042b6af50687f20d2f7b75163a0dd99af0181b

Observation 49f79392-dd48-468a-a2a1-f6db8d99afdd · outbound

This paper cites Code Llama: Open Foundation Models for Code.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation Code Llama: Open Foundation Models for Code

Reference 15

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.068428Z digest=sha256:11f4f7662611462d57e1f917cc49ba59d53cf89bc9da65a615b1d373700991ef

Observation 119594e4-b6b7-493c-a32f-87745aeb9f8e · outbound

This paper cites The llama 3 herd of models,.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation The llama 3 herd of models,

Reference 16

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no resolver link, observed 2026-08-15T21:22:19.073677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.073677Z digest=sha256:73cf19fb5a82f1201ee80ebfc4ad5d57e3c8476395a69857ab55dcfd0b98ad39

Observation af981f6a-d750-4d4b-b36c-f02e582510f8 · outbound

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

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation StarCoder 2 and The Stack v2: The Next Generation

Reference 17

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no resolver link, observed 2026-08-15T21:22:19.084505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.084505Z digest=sha256:84e687ebbe143d10c8702566ae56a01f35ced8f78f4ac13e4a66e7fdd71bedcc

Observation cb0f0e8f-8a17-40f3-8e18-fc2d25eadc06 · outbound

This paper cites Compilable Neural Code Generation with Compiler Feedback.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation Compilable Neural Code Generation with Compiler Feedback

Reference 18

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no resolver link, observed 2026-08-15T21:22:19.089740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.089740Z digest=sha256:d2e8a42de853209f9c15eed4fde24c492512f96f889df39f3bd1384bdf9cfa52

Observation 69dae1c7-ab8c-4e3f-80ad-9546c12b0e14 · outbound

This paper cites CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning

Reference 19

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source=pdf_text observed=2026-08-15T21:22:19.094558Z digest=sha256:b861de94782bbf1acd558c7f559137aee4bf100d939430a7d11b605bdd278cf9

Observation 3bedd0d8-c3b0-47e7-9bdc-1e3bdded469b · outbound

This paper cites CodeDPO: Aligning Code Models with Self Generated and Verified Source Code.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation CodeDPO: Aligning Code Models with Self Generated and Verified Source Code

Reference 20

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source=pdf_text observed=2026-08-15T21:22:19.100005Z digest=sha256:1ca8ebd7f2ab8901df8f185af90b56158c997536f315808db60edfd82d4e8b16

Observation bc6f4f77-45ab-4ab9-a7fd-029aa5c20698 · outbound

This paper cites Learning to reason with large language models.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation Learning to reason with large language models

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:22:19.650894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:22:19.104899Z digest=sha256:98a0109fecfb128a36617e9ce792b94bfe15269f27bd4ae1143b48207f0f4a04

Observation ad362d39-9c82-4b3c-b727-12467efd3026 · outbound

This paper cites Qwq-32b-preview.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation Qwq-32b-preview

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:22:19.635440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:22:19.109445Z digest=sha256:0454d6c724d5e6c01d61cc4dd44dae6fc92e901b4580b95c4c873abc4e925a18

Observation 05764619-47b7-4e38-9e62-f893be94460c · outbound

This paper cites Process Supervision-Guided Policy Optimization for Code Generation.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation Process Supervision-Guided Policy Optimization for Code Generation

Reference 23

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source=pdf_text observed=2026-08-15T21:22:19.113985Z digest=sha256:4e7281dbc85e23e164ba67af1add4c8089ca0ae7bcd3e5bb124816be0f540c90

Observation a0a6640d-1baa-48c2-9be6-48915f57311c · outbound

This paper cites o1-Coder: an o1 Replication for Coding.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation o1-Coder: an o1 Replication for Coding

Reference 24

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source=pdf_text observed=2026-08-15T21:22:19.119076Z digest=sha256:67f0ef676361731ef80da531e603ed446d6c0aac62532380f1631e4729bf2556

Observation 59467b44-aa29-435c-bded-98d44f225b1f · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 25

Resolution
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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.124156Z digest=sha256:6d7363995134766f1f9b5c1714d39be168e6f05d6780312187fdd8e48b435905

Observation ac7b7bf2-aa52-44e2-a622-8c2760e801fc · outbound

This paper cites Step-dpo: Step-wise preference optimization for long-chain reasoning of llms,.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation Step-dpo: Step-wise preference optimization for long-chain reasoning of llms,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:22:19.619608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:22:19.129667Z digest=sha256:4d610e783c3a048e653f73a45580d5808c9e6797d675616cc336ec3201bd6134

Observation ef2701fa-8b87-405e-9596-b2a6a2e94294 · outbound

This paper cites DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-15T21:22:19.139788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.139788Z digest=sha256:59a80f1d0c4d3d346f440e5931e810ac4e6f7266a63674f22b8d0def526c0e20

Observation 760fa94c-8fe6-4107-ba6b-d26cc0667127 · outbound

This paper cites Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-15T21:22:19.134458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.134458Z digest=sha256:508994ba0fbec46b2f6419c92b76e142714e606c4c6159e1edb915670db39403

Observation e25c6fda-9932-4fa8-a1d8-14274e922e93 · outbound

This paper cites Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-15T21:22:19.144150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.144150Z digest=sha256:5350310a1d9bd5491435ce85d61d5cceb1641285327f9775d07d30737bc4b08c

Observation c8b1647e-4183-4857-aeb0-3793662e2154 · outbound

This paper cites an unresolved cited work.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:22:19.602022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:22:19.148389Z digest=sha256:9fd28beb90394242735c0409195712019487f0bd126d973d39d5a9a8f331df8f

Observation 11324b7e-7c75-4a5f-902e-28698d6d1270 · outbound

This paper cites intent":.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation intent":

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:22:19.586212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:22:19.152777Z digest=sha256:9045336ab5814d36474196b7d615b53f08fddcbc5b83c0cad2614baaa4c68ee6

Observation c0000d0d-d641-4e14-b532-3e8b8510e1ad · outbound

This paper cites The Llama 3 Herd of Models.

CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation The Llama 3 Herd of Models

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-15T21:22:19.079364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:22:19.079364Z digest=sha256:70b3b5484a41d0e41cf875e5d954e398944cf4ff008a4c6e9ce239db230af053

Pith citing papers

Observation 48e8e00a-c10c-4ad6-87d5-ebc1e200d6e8 · inbound

Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code cites this paper.

Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code CRPE: Expanding The Reasoning Capability of Large Language Model for Code Generation

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:21:10.770401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-08T17:37:51.790000Z digest=sha256:15d2aa51efc98123bc0b7bde59d126ac8efa602cc235246a4874093bd007e78a