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Paper Citation Record · LEDGER

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review

As of 8 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2506.00296.

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

pith.paper-citation-record.v1
2506.00296 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:13:31.535259Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved34
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0a37f985-df76-41b4-b758-d99c49668c08 · outbound

This paper cites URL: " 'urlintro :=.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review URL: " 'urlintro :=

Reference 1

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source=arxiv_source observed=2026-08-07T12:13:27.819894Z digest=sha256:0d7ba96bcf7a023c75a518ca200797f09a01e82b28fae4bbd49a10aa8f140247

Observation 409171b2-fc51-410d-b2ef-322429ab9c7e · outbound

This paper cites write newline.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review write newline

Reference 2

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source=arxiv_source observed=2026-08-07T12:13:27.868037Z digest=sha256:af208b5d3aa66cf7823d31351c20107f76a6c49efd46952b5d1b16d6ee0a59e3

Observation 1226788f-182f-4901-b966-5447b3b1dbb4 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Constitutional AI: Harmlessness from AI Feedback

Reference 3

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source=arxiv_source observed=2026-08-07T12:13:27.955998Z digest=sha256:b05e5088e6cf01491c9989de7545da61ee74222e7cffe89467f758117248112c

Observation 66f96338-bf22-44e1-af7e-f60e92c2f523 · outbound

This paper cites CodeT: Code Generation with Generated Tests.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review CodeT: Code Generation with Generated Tests

Reference 4

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source=arxiv_source observed=2026-08-07T12:13:28.041024Z digest=sha256:b0c5cc2220f96e5b9bce1e3cc0774ed6dec4206e12e8af52d72c48caccc76978

Observation d5201cf0-82e2-40c3-9b48-2f0f7f9a2223 · outbound

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

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Process Supervision-Guided Policy Optimization for Code Generation

Reference 5

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source=arxiv_source observed=2026-08-07T12:13:28.131857Z digest=sha256:4b96b337af9743fd5aa92ee667ef95eb39c9460d779a18f7722bca5242c07faa

Observation 4887bd46-fc39-4dd5-b312-36bb30a7e0e8 · outbound

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

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review StepCoder: Improve Code Generation with Reinforcement Learning from Compiler Feedback

Reference 6

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source=arxiv_source observed=2026-08-07T12:13:28.236569Z digest=sha256:62db16f20d5036f7f15e33c8d83c19be31141cd3a1a4731dd9506616d23c0bc5

Observation e80f16b5-a0d7-4e28-8ca4-bc5bcf4d98a9 · outbound

This paper cites an unresolved cited work.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Unresolved cited work

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:13:28.338992Z digest=sha256:c7434d7e7f3927d3c261d049d72671eadf68c63a14a3ea7fb5de4339d74da444

Observation d85c020e-2b9f-4eab-839a-fdb88376e34c · outbound

This paper cites ReTool: Reinforcement Learning for Strategic Tool Use in LLMs.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review ReTool: Reinforcement Learning for Strategic Tool Use in LLMs

Reference 8

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source=arxiv_source observed=2026-08-07T12:13:28.430295Z digest=sha256:d863f13597ef58096128e141b49453a374b19251a830c238801cddd27dd4b385

Observation c96330a2-5f5e-4403-b8c0-954be3c8e936 · outbound

This paper cites Synthetic Data Generation & Multi-Step RL for Reasoning & Tool Use.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Synthetic Data Generation & Multi-Step RL for Reasoning & Tool Use

Reference 9

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source=arxiv_source observed=2026-08-07T12:13:28.578751Z digest=sha256:dd3b67857364100ece145683b5e05f7ce14a4a2b382da7c3da7026215f6cd6ba

Observation 9a4f0a3c-c7f6-404d-8446-79094505de63 · outbound

This paper cites From Code to Courtroom: LLMs as the New Software Judges.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review From Code to Courtroom: LLMs as the New Software Judges

Reference 11

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source=arxiv_source observed=2026-08-07T12:13:28.712917Z digest=sha256:824bc7d40c4bc1eb7881ba40c8889db79c03abe61c9744f69d6c2f06e5e2aeb8

Observation 743a6e27-1580-4f63-8809-6e8b24a4334d · outbound

This paper cites Qwen2.5-Coder Technical Report.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Qwen2.5-Coder Technical Report

Reference 12

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source=arxiv_source observed=2026-08-07T12:13:28.766693Z digest=sha256:4815250c4871c3b9f16ecb06ffacf4d155c9b0ece4536a551a2ae134a796c819

Observation 0891ab40-109b-405c-8711-a0ca8d557998 · outbound

This paper cites Combining Large Language Models with Static Analyzers for Code Review Generation.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Combining Large Language Models with Static Analyzers for Code Review Generation

Reference 15

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source=arxiv_source observed=2026-08-07T12:13:28.983443Z digest=sha256:83894b98df7bb0646efbf55c725c05176372ac509115af78ca8a0c4f80c1fcfa

Observation b8e9ab3b-f30f-4602-84c9-cc48cf655b2c · outbound

This paper cites Adam: A Method for Stochastic Optimization.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Adam: A Method for Stochastic Optimization

Reference 16

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source=arxiv_source observed=2026-08-07T12:13:29.031582Z digest=sha256:02301846508bec2d39409304da5e0f15c82d2f92acca1aec235d3a9c487f3359

Observation 85f51358-c0ed-4505-8607-ca85f02cf7b5 · outbound

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

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning

Reference 17

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source=arxiv_source observed=2026-08-07T12:13:29.097459Z digest=sha256:a7cc6aa05dd9b413dc52b958ce4f1e23d7715ccb719f08401a50e4702554077c

Observation 2cff6e52-276b-4b3c-a851-34cd9e6bf3db · outbound

This paper cites RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

Reference 18

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source=arxiv_source observed=2026-08-07T12:13:29.156891Z digest=sha256:8b07e9070afa90412d14456edb5217f16aea497385a8def6eb0f2357c5fbcc31

Observation 258094e3-3a3b-4a44-989f-2d981cd83ba1 · outbound

This paper cites START: Self-taught Reasoner with Tools.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review START: Self-taught Reasoner with Tools

Reference 19

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source=arxiv_source observed=2026-08-07T12:13:29.255727Z digest=sha256:04d1f74bc2efc4bcb77ef8a0f617b52502b771636c133cbf95b409a91d335a72

Observation f5e3900a-9297-45a1-aaae-43a679319d82 · outbound

This paper cites Automating Code Review Activities by Large-Scale Pre-training.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Automating Code Review Activities by Large-Scale Pre-training

Reference 20

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source=arxiv_source observed=2026-08-07T12:13:29.354978Z digest=sha256:5ccc716d514ec5bac5bc4d7e2728fa0f127a5463fc1acc2c4d03a3305ad826a5

Observation 8f783172-ae83-40f5-88c7-ff51dfa864c0 · outbound

This paper cites CodeReviewQA: The Code Review Comprehension Assessment for Large Language Models.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review CodeReviewQA: The Code Review Comprehension Assessment for Large Language Models

Reference 21

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source=arxiv_source observed=2026-08-07T12:13:29.461653Z digest=sha256:5999dc6d1dc4f56f7cad7bb6853e74436f9b17c236362cc4a236f40631e6d8c7

Observation be73da4c-922a-40dd-9db0-228a4ac094ad · outbound

This paper cites an unresolved cited work.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Unresolved cited work

Reference 22

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source=arxiv_source observed=2026-08-07T12:13:29.587582Z digest=sha256:5c9d55f58800435e87e9aa4d5d37ca0bb16d0dbc5e99d3bec5857f75c6578ee1

Observation b36489cf-d06b-4897-b3c9-75ceb9958269 · outbound

This paper cites LLM Critics Help Catch LLM Bugs.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review LLM Critics Help Catch LLM Bugs

Reference 23

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source=arxiv_source observed=2026-08-07T12:13:29.658971Z digest=sha256:9f80bacf74cc9290fc407f587cf4e417c9e52241dec4a84dd9a854660230e14d

Observation 65e25777-c9b6-4f62-9b7f-ab38f36f03f7 · outbound

This paper cites an unresolved cited work.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Unresolved cited work

Reference 24

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source=arxiv_source observed=2026-08-07T12:13:29.764224Z digest=sha256:b22d559c5f6895307873000fc94468244637037507f09e3fdcaf517129ee70e7

Observation 4dbb1b94-8cec-436c-a2be-f160f0de76b5 · outbound

This paper cites CRScore: Grounding Automated Evaluation of Code Review Comments in Code Claims and Smells.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review CRScore: Grounding Automated Evaluation of Code Review Comments in Code Claims and Smells

Reference 25

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source=arxiv_source observed=2026-08-07T12:13:29.842064Z digest=sha256:10bc00f45ecabe7ee50bbb7f9c2dca7c942d43a50bf7941ff976d9576433d409

Observation 3e89c7ac-da89-4fb0-bd0e-994a93027189 · outbound

This paper cites an unresolved cited work.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Unresolved cited work

Reference 26

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:13:29.965945Z digest=sha256:d43b455ba2505f8d6f26a3dfb21bf8efd65b599137aad1c8d0caf60e636f2785

Observation 5e9e2e5f-3572-4fa8-ac88-f7c9925f3aba · outbound

This paper cites GPT-4 Technical Report.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review GPT-4 Technical Report

Reference 27

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source=arxiv_source observed=2026-08-07T12:13:30.074007Z digest=sha256:83351bc7cdfcc6ee355153e1daa3cbe6f2817a8b7a5efb8a5c63f9062fd3a176

Observation be6c9dcb-e057-4499-9684-0710c2887e4e · outbound

This paper cites Training language models to follow instructions with human feedback.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Training language models to follow instructions with human feedback

Reference 28

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source=arxiv_source observed=2026-08-07T12:13:30.281460Z digest=sha256:28b771a24592af5a6d55cd48a6420c551a52e3eac54b0495fefb9848cfc4dc56

Observation ae569631-9770-4863-9f1b-e9e18ee77ac7 · outbound

This paper cites an unresolved cited work.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Unresolved cited work

Reference 29

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:13:30.389698Z digest=sha256:8dc9e2b3930f89181f7b93c8367b6b79dcf84022dbb74412bf33d73b4a334a8b

Observation 4ea2b124-12f3-47a5-9f30-e1082b033ea4 · outbound

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

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 30

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source=arxiv_source observed=2026-08-07T12:13:30.494844Z digest=sha256:3da2ee9b41010688d7a9e5a7e1175c7bf442a845cba18558887b4dd81d6ce0b4

Observation 840fba43-2526-49e2-a957-e5724f145d6b · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 31

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source=arxiv_source observed=2026-08-07T12:13:30.620350Z digest=sha256:b7a9d8ee9413a4cb17c1ed4cd1b5055d74d7e80ea90ab85098068197e824e6b2

Observation fa8155ff-2c86-43e0-a9c9-fa60d5157140 · outbound

This paper cites an unresolved cited work.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Unresolved cited work

Reference 32

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:13:30.739759Z digest=sha256:159500504cd8641759c0717a92466b3150646bd5047e64f631d875cc8039320d

Observation a6b33dcb-853a-4353-a238-205e085770ba · outbound

This paper cites an unresolved cited work.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Unresolved cited work

Reference 33

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source=arxiv_source observed=2026-08-07T12:13:30.883955Z digest=sha256:2d7730982b8495ae3f0cb6f28d67f1265064ce92cd7d160eb6c4aa626c4f84a1

Observation e4ab76c1-9d04-43bf-83d5-17e42bb72453 · outbound

This paper cites A Survey on Machine Learning Techniques for Source Code Analysis.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review A Survey on Machine Learning Techniques for Source Code Analysis

Reference 34

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source=arxiv_source observed=2026-08-07T12:13:30.996063Z digest=sha256:e662da286866c6ec05e40738d61875f9cfbc5d0aa9638d6f98cfd264cb477eb9

Observation e5205a5a-af31-4ef0-8d55-44c38a1114d2 · outbound

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

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Execution-based Code Generation using Deep Reinforcement Learning

Reference 35

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source=arxiv_source observed=2026-08-07T12:13:31.122727Z digest=sha256:696351c20937001d638f4c5d56b52ede212beb84fee0b7e8d3ed41fd0f07a68a

Observation 60aaf661-9633-42ec-b9f9-77c98f4f59bc · outbound

This paper cites an unresolved cited work.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Unresolved cited work

Reference 36

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:13:31.209972Z digest=sha256:17fa1c14ee831e048dce59d913a4d21fc5b340d71c03c72ee7bae3992143e24e

Observation ac31a24c-c423-4aa8-bf6f-cc421c3367c4 · outbound

This paper cites Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineering.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineering

Reference 38

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source=arxiv_source observed=2026-08-07T12:13:31.407675Z digest=sha256:2be81b5e63fb5be87c5cf64dcb84f48b4ebb135b51b66822cfa12c17af700466

Observation bab77ff3-568d-41f8-9017-dbb0cfde314f · outbound

This paper cites Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

Reference 39

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source=arxiv_source observed=2026-08-07T12:13:31.535259Z digest=sha256:66e43871fb3215aacb76cca4b6104db5d102f496b2491cb40596db25c36d8063

Pith citing papers

No inbound Pith citation observations are available.