Paper Citation Record · LEDGER

Process-Supervised Reinforcement Learning for Code Generation

As of 10 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 9 inbound Pith citation observations for arXiv:2502.01715.

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

pith.paper-citation-record.v1
2502.01715 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T15:10:39.001050Z

measured 63 of 63 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:31:54.286136Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T12:44:40.230064Z

Reference resolution

54 of 54 outbound references displayed

verified exact3
verified fuzzy0
unresolved51
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 44db55d9-7fb6-4803-94ee-e4ec4ec07176 · outbound

This paper cites GPT-4 Technical Report.

Process-Supervised Reinforcement Learning for Code Generation GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.746645Z

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Observation 0056b658-88b8-42cb-8aff-613fa78adb8a · outbound

This paper cites an unresolved cited work.

Process-Supervised Reinforcement Learning for Code Generation Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.751842Z

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Observation 6c32569f-3a9d-4705-8abf-cf0b3e87ab48 · outbound

This paper cites Concrete Problems in AI Safety.

Process-Supervised Reinforcement Learning for Code Generation Concrete Problems in AI Safety

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.757164Z

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Observation 20a2211f-d9c2-46ed-8157-fb84d8f6dae9 · outbound

This paper cites Program Synthesis with Large Language Models.

Process-Supervised Reinforcement Learning for Code Generation Program Synthesis with Large Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.762277Z

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Observation c367e2ca-b73d-4664-a06f-075c3c6e5282 · outbound

This paper cites Language Models are Few-Shot Learners.

Process-Supervised Reinforcement Learning for Code Generation Language Models are Few-Shot Learners

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.767129Z

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Observation 81b336dd-1a86-4be9-b198-ad2b53e51433 · outbound

This paper cites Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback.

Process-Supervised Reinforcement Learning for Code Generation Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.772031Z

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Observation 11ed19ae-6dd5-4a38-9bfb-088af0c68af3 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Process-Supervised Reinforcement Learning for Code Generation Evaluating Large Language Models Trained on Code

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.777654Z

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Observation 9cb63d96-72bc-49c9-bfb8-cbba843e0a92 · outbound

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

Process-Supervised Reinforcement Learning for Code Generation Process Supervision-Guided Policy Optimization for Code Generation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.782468Z

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Observation 763fd09c-214a-4f75-8455-fa3a916adb48 · outbound

This paper cites Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access.

Process-Supervised Reinforcement Learning for Code Generation Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.787613Z

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Observation 012cf20e-210f-4178-b988-d7b3b102023c · outbound

This paper cites The Llama 3 Herd of Models.

Process-Supervised Reinforcement Learning for Code Generation The Llama 3 Herd of Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.792717Z

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Observation 7b976b9b-1e7e-4b0a-b036-cab8504a3c38 · outbound

This paper cites CodeBERT: A Pre-Trained Model for Programming and Natural Languages.

Process-Supervised Reinforcement Learning for Code Generation CodeBERT: A Pre-Trained Model for Programming and Natural Languages

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.797764Z

Source-reported events for the cited work

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Observation 477ad882-2a87-40b3-bdf6-9882e2eac1a4 · outbound

This paper cites an unresolved cited work.

Process-Supervised Reinforcement Learning for Code Generation Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.802256Z

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Observation 38f56300-3a0c-407c-9728-b45cdc92ef5e · outbound

This paper cites UniXcoder: Unified Cross-Modal Pre-training for Code Representation.

Process-Supervised Reinforcement Learning for Code Generation UniXcoder: Unified Cross-Modal Pre-training for Code Representation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.807462Z

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Observation 06359d2f-5ce0-4aab-8cf5-1c94af8c2df3 · outbound

This paper cites GraphCodeBERT: Pre-training Code Representations with Data Flow.

Process-Supervised Reinforcement Learning for Code Generation GraphCodeBERT: Pre-training Code Representations with Data Flow

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.812077Z

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Observation bbab7549-6628-4783-8e7e-9fd8ec298cdd · outbound

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

Process-Supervised Reinforcement Learning for Code Generation DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.816815Z

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Observation 15a9ec98-f86f-4d15-b564-d810cf708beb · outbound

This paper cites an unresolved cited work.

Process-Supervised Reinforcement Learning for Code Generation Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-09T15:10:39.783815Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e7c9a691-87fa-4cf0-b645-0c8c88e73e3c · outbound

This paper cites an unresolved cited work.

Process-Supervised Reinforcement Learning for Code Generation Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-09T15:10:39.767454Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7d60ab94-c0e6-4cd8-ba32-9e9591c08c3b · outbound

This paper cites A Survey on Large Language Models for Code Generation.

Process-Supervised Reinforcement Learning for Code Generation A Survey on Large Language Models for Code Generation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.830590Z

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Observation 2d0c8187-abce-4049-8641-ef4c0fcd7ff7 · outbound

This paper cites an unresolved cited work.

Process-Supervised Reinforcement Learning for Code Generation Unresolved cited work

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.835716Z

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Observation ec13d256-b9ae-4e69-b018-ec4e62afcfd8 · outbound

This paper cites an unresolved cited work.

Process-Supervised Reinforcement Learning for Code Generation Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-09T15:10:39.741845Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8dbd8ac3-f10b-4ffe-a237-a13a61f4b112 · outbound

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

Process-Supervised Reinforcement Learning for Code Generation RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.844627Z

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Observation d0aa659f-55d3-41eb-a76e-edc90acd3175 · outbound

This paper cites StarCoder: may the source be with you!.

Process-Supervised Reinforcement Learning for Code Generation StarCoder: may the source be with you!

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.849701Z

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Observation 54c0398b-cf32-4f36-a34d-92907d7de799 · outbound

This paper cites an unresolved cited work.

Process-Supervised Reinforcement Learning for Code Generation Unresolved cited work

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.854560Z

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Observation 777d1184-b482-4e03-8384-2d3dddb99d23 · outbound

This paper cites Let's Verify Step by Step.

Process-Supervised Reinforcement Learning for Code Generation Let's Verify Step by Step

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.859562Z

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Observation bf02f726-c214-480a-b365-4b18e1a0c4ea · outbound

This paper cites an unresolved cited work.

Process-Supervised Reinforcement Learning for Code Generation Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-09T15:10:39.716141Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 399b8bb8-37a4-4c0a-aa2f-376e220713c2 · outbound

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

Process-Supervised Reinforcement Learning for Code Generation RLTF: Reinforcement Learning from Unit Test Feedback

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.868972Z

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Observation da135484-570d-4fc5-b66b-a249d7f9f50f · outbound

This paper cites Improve Mathematical Reasoning in Language Models by Automated Process Supervision.

Process-Supervised Reinforcement Learning for Code Generation Improve Mathematical Reasoning in Language Models by Automated Process Supervision

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.874401Z

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Observation 54fc7869-4a4c-4613-8f6a-c6c38907ce13 · outbound

This paper cites Let's reward step by step: Step-Level reward model as the Navigators for Reasoning.

Process-Supervised Reinforcement Learning for Code Generation Let's reward step by step: Step-Level reward model as the Navigators for Reasoning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.879367Z

Source-reported events for the cited work

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Observation 0aedf4ac-34bd-41ce-b874-7a9d7fb118cc · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

Process-Supervised Reinforcement Learning for Code Generation Playing Atari with Deep Reinforcement Learning

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.884186Z

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Observation bd164991-ce4a-49c2-b077-7b6446eb505f · outbound

This paper cites an unresolved cited work.

Process-Supervised Reinforcement Learning for Code Generation Unresolved cited work

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.889088Z

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Observation a5cf2432-338a-4442-be1d-5965b8d2d9a3 · outbound

This paper cites CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis.

Process-Supervised Reinforcement Learning for Code Generation CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.893567Z

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Observation b48f425f-3241-492f-b801-20288909d7d8 · outbound

This paper cites an unresolved cited work.

Process-Supervised Reinforcement Learning for Code Generation Unresolved cited work

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.898254Z

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Observation 9534e56e-ce12-4d14-934f-789adc462854 · outbound

This paper cites an unresolved cited work.

Process-Supervised Reinforcement Learning for Code Generation Unresolved cited work

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.903595Z

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Observation 7519ed64-db05-4ee2-9168-3ce1d56b98da · outbound

This paper cites CodeBLEU: a Method for Automatic Evaluation of Code Synthesis.

Process-Supervised Reinforcement Learning for Code Generation CodeBLEU: a Method for Automatic Evaluation of Code Synthesis

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.908142Z

Source-reported events for the cited work

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Observation 9dd5e846-051b-45f2-ae80-93322471ba29 · outbound

This paper cites an unresolved cited work.

Process-Supervised Reinforcement Learning for Code Generation Unresolved cited work

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.913160Z

Source-reported events for the cited work

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Observation b22b0fb4-2ea6-45f7-9200-0afb4b0bd28a · outbound

This paper cites Proximal Policy Optimization Algorithms.

Process-Supervised Reinforcement Learning for Code Generation Proximal Policy Optimization Algorithms

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.917519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e62896b-58e7-403e-bc94-5d8f11da6227 · outbound

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

Process-Supervised Reinforcement Learning for Code Generation Execution-based Code Generation using Deep Reinforcement Learning

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.922030Z

Source-reported events for the cited work

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Observation 54915dd4-887f-4690-9423-85276bffe2ee · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Process-Supervised Reinforcement Learning for Code Generation LLaMA: Open and Efficient Foundation Language Models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.926569Z

Source-reported events for the cited work

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Observation 4625abeb-b736-42cf-8643-24031b2b9917 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Process-Supervised Reinforcement Learning for Code Generation Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.930919Z

Source-reported events for the cited work

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Observation f9f01a97-994a-4618-afa8-76c2534bdf8e · outbound

This paper cites Solving math word problems with process- and outcome-based feedback.

Process-Supervised Reinforcement Learning for Code Generation Solving math word problems with process- and outcome-based feedback

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.935579Z

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Observation 81c24362-4f0a-4cdb-9134-116180b7db97 · outbound

This paper cites an unresolved cited work.

Process-Supervised Reinforcement Learning for Code Generation Unresolved cited work

Reference 41

Resolution: unresolved; raw_fallback, observed 2026-08-09T15:10:39.661393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8454ba4b-efd8-41b4-840c-51b2d9f2ff55 · outbound

This paper cites an unresolved cited work.

Process-Supervised Reinforcement Learning for Code Generation Unresolved cited work

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.944659Z

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Observation 247ed4be-1511-457e-b6a0-261ed9b59708 · outbound

This paper cites Compilable Neural Code Generation with Compiler Feedback.

Process-Supervised Reinforcement Learning for Code Generation Compilable Neural Code Generation with Compiler Feedback

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-08-09T15:10:39.157183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0cc9f4bb-5586-44e6-9fab-b4b98adca092 · outbound

This paper cites CodeT5+: Open Code Large Language Models for Code Understanding and Generation.

Process-Supervised Reinforcement Learning for Code Generation CodeT5+: Open Code Large Language Models for Code Understanding and Generation

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.953669Z

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Observation 626d8ee4-88f9-42ef-92a6-01ac4b2928b1 · outbound

This paper cites CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation.

Process-Supervised Reinforcement Learning for Code Generation CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.958717Z

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Observation 054dac79-5ce3-4e3c-8023-ddb7455b472f · outbound

This paper cites Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning.

Process-Supervised Reinforcement Learning for Code Generation Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-08-09T15:10:39.104213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b102dee4-1e04-41d4-8eb8-727ec912214f · outbound

This paper cites Recursively Summarizing Books with Human Feedback.

Process-Supervised Reinforcement Learning for Code Generation Recursively Summarizing Books with Human Feedback

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.967859Z

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Observation 068badc7-02e3-4791-a5a0-d8c04c9de420 · outbound

This paper cites an unresolved cited work.

Process-Supervised Reinforcement Learning for Code Generation Unresolved cited work

Reference 48

Resolution: unresolved; raw_fallback, observed 2026-08-09T15:10:39.635553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 88e70d61-df5f-4499-8ba5-0301212479d5 · outbound

This paper cites an unresolved cited work.

Process-Supervised Reinforcement Learning for Code Generation Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-08-09T15:10:39.618283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a0fe9872-cd95-4a06-aca8-11e1f8c28c74 · outbound

This paper cites Large Language Models Meet NL2Code: A Survey.

Process-Supervised Reinforcement Learning for Code Generation Large Language Models Meet NL2Code: A Survey

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.981032Z

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Observation fb166f4f-8517-4990-9242-8b043d6b6f61 · outbound

This paper cites an unresolved cited work.

Process-Supervised Reinforcement Learning for Code Generation Unresolved cited work

Reference 51

Resolution: verified exact; doi, observed 2026-08-09T15:10:39.039045Z

Source-reported events for the cited work

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Observation a443e119-8987-407d-b456-34cff9e5173a · outbound

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

Process-Supervised Reinforcement Learning for Code Generation Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.991652Z

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Observation 2c9d9588-16f3-47b8-af7f-3226fbbdbd79 · outbound

This paper cites online" 'onlinestring :=.

Process-Supervised Reinforcement Learning for Code Generation online" 'onlinestring :=

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:38.996261Z

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Unavailable: canonical work link unavailable.

Observation 9d8e089c-8dda-4b85-9f4c-c38fd3e6e9a2 · outbound

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Process-Supervised Reinforcement Learning for Code Generation write newline

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-09T15:10:39.001050Z

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Pith citing papers

Observation 18e4674b-e365-46e7-8ec7-e59fadbb27af · inbound

Improving LLM-Generated Code Quality with GRPO cites this paper.

Improving LLM-Generated Code Quality with GRPO Process-Supervised Reinforcement Learning for Code Generation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T11:31:54.286136Z

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Observation aaffbf05-6329-479d-bf10-f10098639611 · inbound

Reinforcement Learning in hyperbolic space for multi-step reasoning cites this paper.

Reinforcement Learning in hyperbolic space for multi-step reasoning Process-Supervised Reinforcement Learning for Code Generation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T15:24:25.819837Z

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Observation 1ebf6c85-9541-44f4-ba5d-45ae9cf8dc64 · inbound

Reinforcement Learning Improves Traversal of Parametric Knowledge in LLMs cites this paper.

Reinforcement Learning Improves Traversal of Parametric Knowledge in LLMs Process-Supervised Reinforcement Learning for Code Generation

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-03T23:27:38.089096Z

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Observation 862d71d8-3201-45e2-a169-e6611ec11551 · inbound

Beyond Binary: Turning Partial Success into Dense Verifiable Rewards for Reinforcement Learning in Code Generation cites this paper.

Beyond Binary: Turning Partial Success into Dense Verifiable Rewards for Reinforcement Learning in Code Generation Process-Supervised Reinforcement Learning for Code Generation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T12:19:35.177823Z

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Observation e0374b31-8d81-4623-8e1e-6d44d37a3bfb · inbound

TestDecision: Sequential Test Suite Generation via Greedy Optimization and Reinforcement Learning cites this paper.

TestDecision: Sequential Test Suite Generation via Greedy Optimization and Reinforcement Learning Process-Supervised Reinforcement Learning for Code Generation

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-05-13T21:38:18.788744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6a3feea1-6dfe-49be-aa00-6b9d94158540 · inbound

Free Energy-Driven Reinforcement Learning with Adaptive Advantage Shaping for Unsupervised Reasoning in LLMs cites this paper.

Free Energy-Driven Reinforcement Learning with Adaptive Advantage Shaping for Unsupervised Reasoning in LLMs Process-Supervised Reinforcement Learning for Code Generation

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:45:59.984342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cd0ae5ae-5a2c-43c2-abbf-20c4a72c161e · inbound

Adapt to Thrive! Adaptive Power-Mean Policy Optimization for Improved LLM Reasoning cites this paper.

Adapt to Thrive! Adaptive Power-Mean Policy Optimization for Improved LLM Reasoning Process-Supervised Reinforcement Learning for Code Generation

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:01:00.233468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1d03fe18-37d5-47bd-8db7-482b1e88f803 · inbound

Beyond Trajectory Rewards: Step-level Credit Assignment for Agentic Search via Graph Modeling cites this paper.

Beyond Trajectory Rewards: Step-level Credit Assignment for Agentic Search via Graph Modeling Process-Supervised Reinforcement Learning for Code Generation

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-06-29T08:03:14.288936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fae0bdb1-6d17-4048-8adb-07a787463b99 · inbound

BV-Blend: Uncertainty-Weighted Historical Baselines for Stable Critic-Free RL with Verifiable Rewards cites this paper.

BV-Blend: Uncertainty-Weighted Historical Baselines for Stable Critic-Free RL with Verifiable Rewards Process-Supervised Reinforcement Learning for Code Generation

Reference 105

Resolution: verified exact; arxiv_id, observed 2026-06-30T12:44:40.231715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.