Paper Citation Record · LEDGER

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training

As of 7 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 9 inbound Pith citation observations for arXiv:2507.12507.

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

pith.paper-citation-record.v1
2507.12507 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:51:43.099838Z

measured 42 of 42 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T04:39:04.024925Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T20:56:13.554863Z

Reference resolution

33 of 33 outbound references displayed

verified exact0
verified fuzzy14
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 01702ac7-f90e-41df-ad01-e3366eed0b87 · outbound

This paper cites OpenAI o1 System Card.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training OpenAI o1 System Card

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:41.308878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b91c1ff4-f3e1-4e84-836e-c7ef764722fb · outbound

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

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:41.379398Z

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Observation 9cd6446e-a56c-4d76-832e-a6d630ed29b0 · outbound

This paper cites Tang, Manan Roongta, Colin Cai, Jef- frey Luo, Li Erran Li, Raluca Ada Popa, and Ion Stoica.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Tang, Manan Roongta, Colin Cai, Jef- frey Luo, Li Erran Li, Raluca Ada Popa, and Ion Stoica

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:51:44.536753Z

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

Observation ae443173-a672-4bb6-87ec-464a477d3bef · outbound

This paper cites Dapo: An open-source llm reinforcement learning system at scale, 2025.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Dapo: An open-source llm reinforcement learning system at scale, 2025

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:41.605352Z

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Observation d72de7c8-7f04-4e43-b906-ee8f2bc20d39 · outbound

This paper cites Process Reinforcement through Implicit Rewards.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Process Reinforcement through Implicit Rewards

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:41.675432Z

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Unavailable: canonical work link unavailable.

Observation e3eded81-4d23-4ab7-abbf-2568a743311f · outbound

This paper cites Scp-116k: A high-quality problem-solution dataset and a generalized pipeline for automated extraction in the higher education science domain, 2025.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Scp-116k: A high-quality problem-solution dataset and a generalized pipeline for automated extraction in the higher education science domain, 2025

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:41.754532Z

Source-reported events for the cited work

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Observation b7202fe5-07b3-4c21-8477-6aec33c4b1fc · outbound

This paper cites Reasoning gym: Reasoning environments for reinforcement learning with verifiable rewards, 2025.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Reasoning gym: Reasoning environments for reinforcement learning with verifiable rewards, 2025

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:51:44.440037Z

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.

Observation e2d45004-e28f-4f90-b895-4a4bf75b0781 · outbound

This paper cites an unresolved cited work.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:51:44.361140Z

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.

Observation 6c2e0656-9b38-4af2-8d61-d9e6fb88c713 · outbound

This paper cites Instruction-following evaluation for large language models, 2023.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Instruction-following evaluation for large language models, 2023

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:41.986503Z

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Unavailable: canonical work link unavailable.

Observation 73910816-2529-43d4-ba57-7b29a62e8611 · outbound

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

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:42.072510Z

Source-reported events for the cited work

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Observation 38a9ed1a-7369-4098-9a0b-75cbc62aa494 · outbound

This paper cites Proximal policy optimization algorithms, 2017.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Proximal policy optimization algorithms, 2017

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:42.132236Z

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Observation 44a62020-97b4-44bf-b019-693d73a66d65 · outbound

This paper cites Approximating KL Divergence.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Approximating KL Divergence

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:51:44.270150Z

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.

Observation e9f94756-acd8-4fa3-9f76-d3a664121d0b · outbound

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

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Deepcoder: A fully open-source 14b coder at o3-mini level

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:51:44.190811Z

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.

Observation 5036a461-add3-44f6-971b-82c784a0fff8 · outbound

This paper cites Vapo: Efficient and reliable reinforcement learning for advanced reasoning tasks, 2025.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Vapo: Efficient and reliable reinforcement learning for advanced reasoning tasks, 2025

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:51:44.120691Z

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.

Observation 06296c41-5472-4ca1-a519-acb330813ae0 · outbound

This paper cites Skywork open reasoner series.https://capricious-hydrogen-41c .notion.site/Skywork-Open-Reaonser- Series-1d0bc9ae823a80459b46c149e4f51680, 2025.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Skywork open reasoner series.https://capricious-hydrogen-41c .notion.site/Skywork-Open-Reaonser- Series-1d0bc9ae823a80459b46c149e4f51680, 2025

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:51:44.066802Z

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.

Observation 9fb672b9-d13d-4e17-97ff-e2bb93fea91c · outbound

This paper cites Hybridflow: A flexible and efficient rlhf framework.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Hybridflow: A flexible and efficient rlhf framework

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:51:43.928142Z

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.

Observation 1f6e9583-fd27-417e-ae19-f98d530e3e09 · outbound

This paper cites Decoupled weight decay regularization, 2019.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Decoupled weight decay regularization, 2019

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:42.428615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4371198a-3b07-42c5-a489-2af2baca32d0 · outbound

This paper cites 7b model and 8k examples: Emerging reasoning with reinforcement learning is both effective and efficient.https://hkust-nlp.notion.site/ simplerl-reason, 2025.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training 7b model and 8k examples: Emerging reasoning with reinforcement learning is both effective and efficient.https://hkust-nlp.notion.site/ simplerl-reason, 2025

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:51:43.806690Z

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.

Observation 9ec5ac18-d477-4187-bdce-9003b7eb8312 · outbound

This paper cites American invitational mathematics examination - aime.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training American invitational mathematics examination - aime

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:51:43.711163Z

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.

Observation 62f2ad05-1b60-44e6-b401-05a5ffa833e7 · outbound

This paper cites American invitational mathematics examination - aime.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training American invitational mathematics examination - aime

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:51:43.608952Z

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.

Observation ea63ccc2-ada3-4e43-b86d-47132b004ac6 · outbound

This paper cites American mathematics competition - amc.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training American mathematics competition - amc

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:51:43.543312Z

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.

Observation c7028bb1-2669-48a3-b27d-c54cbecb0cb6 · outbound

This paper cites Measuring mathematical problem solving with the math dataset, 2021.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Measuring mathematical problem solving with the math dataset, 2021

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:42.599645Z

Source-reported events for the cited work

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Observation bde776d0-36a9-4c99-a458-dfee812f1963 · outbound

This paper cites Solving quantitative reasoning problems with language models, 2022.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Solving quantitative reasoning problems with language models, 2022

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:42.633994Z

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Observation 58383f93-4bd2-4994-9394-11a5d15a3604 · outbound

This paper cites Olympiadbench: A challenging benchmark for promoting agi with olympiad-level bilingual multimodal scientific problems, 2024.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Olympiadbench: A challenging benchmark for promoting agi with olympiad-level bilingual multimodal scientific problems, 2024

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:42.657244Z

Source-reported events for the cited work

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Observation 43299953-156f-4e44-91f1-fd7833a838ea · outbound

This paper cites Measuring coding challenge competence with apps, 2021.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Measuring coding challenge competence with apps, 2021

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:42.719030Z

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Observation 31cdb266-0bbe-4b21-ba0e-157ff5892789 · outbound

This paper cites Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray Kavukcuoglu, and Oriol Vinyals.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray Kavukcuoglu, and Oriol Vinyals

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:42.778292Z

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Observation 12403a07-828b-4577-9316-ef7bc464d2d8 · outbound

This paper cites Taco: Topics in algorithmic code generation dataset, 2023.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Taco: Topics in algorithmic code generation dataset, 2023

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:42.831655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98a14543-e3ae-4cb7-bccf-8b9d918c770c · outbound

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

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Is your code generated by chatGPT really correct? rigorous evaluation of large language models for code generation

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:51:43.418470Z

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.

Observation ae44f13a-84c5-4e58-82bc-276933a6febe · outbound

This paper cites Livecodebench: Holistic and contamination free evaluation of large language models for code, 2024.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Livecodebench: Holistic and contamination free evaluation of large language models for code, 2024

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:42.887053Z

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Unavailable: canonical work link unavailable.

Observation 202e4379-5d88-4739-af38-9804f644e500 · outbound

This paper cites an unresolved cited work.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Unresolved cited work

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:42.908581Z

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Observation e0df78d3-4be0-4360-8fef-94fdf4fc1630 · outbound

This paper cites Online difficulty filtering for reasoning oriented reinforcement learning, 2025.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Online difficulty filtering for reasoning oriented reinforcement learning, 2025

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:42.984504Z

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Observation bba4a0ec-2391-4fa3-a991-b13230e25b7a · outbound

This paper cites Gonzalez, Hao Zhang, and Ion Stoica.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training Gonzalez, Hao Zhang, and Ion Stoica

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:51:43.341473Z

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

Observation 3573b1db-f3f2-4d53-8cdc-f1b92d7d675d · outbound

This paper cites The curious case of neural text degeneration, 2020.

Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training The curious case of neural text degeneration, 2020

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:51:43.283087Z

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

Pith citing papers

Observation 74b92fd2-80fe-457e-8dfc-f7d363cc0b3b · inbound

Scaling DRL for Decision Making: A Survey on Data, Network, and Training Budget Strategies cites this paper.

Scaling DRL for Decision Making: A Survey on Data, Network, and Training Budget Strategies Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training

Reference 26

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Observation da2f79da-b1fe-4b5c-bc8a-065e3102426e · inbound

Learning to Reason Efficiently with Discounted Reinforcement Learning cites this paper.

Learning to Reason Efficiently with Discounted Reinforcement Learning Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-04T07:59:53.046706Z

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Observation 3310297e-1a88-4046-94cf-424c1b424a51 · inbound

Cognitive Pivot Points and Visual Anchoring: Unveiling and Rectifying Hallucinations in Multimodal Reasoning Models cites this paper.

Cognitive Pivot Points and Visual Anchoring: Unveiling and Rectifying Hallucinations in Multimodal Reasoning Models Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:25:59.026410Z

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.

Observation ddab7b49-4cd9-47a9-8686-07871448f7bd · inbound

Cognitive Pivot Points and Visual Anchoring: Unveiling and Rectifying Hallucinations in Multimodal Reasoning Models cites this paper.

Cognitive Pivot Points and Visual Anchoring: Unveiling and Rectifying Hallucinations in Multimodal Reasoning Models Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-12T22:48:45.647588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19e525d1-700f-4d79-b634-ea8bad51050a · inbound

Generalization in LLM Problem Solving: The Case of the Shortest Path cites this paper.

Generalization in LLM Problem Solving: The Case of the Shortest Path Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-10T10:39:38.040670Z

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.

Observation e5e3e00a-54c4-4420-88fc-74d3b10c6268 · inbound

DISA: Offline Importance Sampling for Distribution-Matching LLM-RL cites this paper.

DISA: Offline Importance Sampling for Distribution-Matching LLM-RL Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-20T15:13:24.864105Z

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.

Observation 087dd9df-be03-46a5-a491-625313e27927 · inbound

ARES: Automated Rubric Synthesis for Scalable LLM Reinforcement Learning cites this paper.

ARES: Automated Rubric Synthesis for Scalable LLM Reinforcement Learning Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-25T04:35:21.594882Z

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

Observation 85b190e6-9899-4bb1-95db-2d694c32d13a · inbound

ARES: Automated Rubric Synthesis for Scalable LLM Reinforcement Learning cites this paper.

ARES: Automated Rubric Synthesis for Scalable LLM Reinforcement Learning Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-06-30T16:24:55.362639Z

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.

Observation 373a9187-b9f6-4da7-8a24-f1581a8da92d · inbound

Trust Region On-Policy Distillation cites this paper.

Trust Region On-Policy Distillation Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training

Reference 226

Resolution: verified exact; arxiv_id, observed 2026-07-01T20:56:13.556324Z

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.