Paper Citation Record · LEDGER

Teaching Large Language Models to Reason with Reinforcement Learning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 43 inbound Pith citation observations for arXiv:2403.04642.

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

pith.paper-citation-record.v1
2403.04642 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 43 of 43 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:11:08.137792Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T02:42:26.083324Z

Reference resolution

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verified exact0
verified fuzzy0
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External citation measurements

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Outbound references

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Pith citing papers

Observation e620d219-e4d2-4d99-b7cc-e5b38a53b4cf · inbound

Training Language Models to Self-Correct via Reinforcement Learning cites this paper.

Training Language Models to Self-Correct via Reinforcement Learning Teaching Large Language Models to Reason with Reinforcement Learning

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-17T12:04:10.444859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5e742e69-9d5d-4e1b-ab04-905424c5eb95 · inbound

Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning cites this paper.

Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning Teaching Large Language Models to Reason with Reinforcement Learning

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-21T01:42:19.179140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 81073105-9561-4640-9bdf-431d133e25bb · inbound

Training Large Language Models to Reason in a Continuous Latent Space cites this paper.

Training Large Language Models to Reason in a Continuous Latent Space Teaching Large Language Models to Reason with Reinforcement Learning

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:29:05.706544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0d0b062e-1036-4c1f-b7fe-403edeb2d6d2 · inbound

Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning cites this paper.

Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning Teaching Large Language Models to Reason with Reinforcement Learning

Reference 10

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Observation 943e4545-6612-4952-a7c6-53c23682a60a · inbound

On the Emergence of Thinking in LLMs I: Searching for the Right Intuition cites this paper.

On the Emergence of Thinking in LLMs I: Searching for the Right Intuition Teaching Large Language Models to Reason with Reinforcement Learning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-08T14:25:53.357179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c98a33f2-13cf-4e37-974c-51909915dc0d · inbound

Process Reward Models for LLM Agents: Practical Framework and Directions cites this paper.

Process Reward Models for LLM Agents: Practical Framework and Directions Teaching Large Language Models to Reason with Reinforcement Learning

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T18:39:38.006409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23390e2f-76d4-4c61-b3fb-2f047a4552c5 · inbound

Learning to Reason at the Frontier of Learnability cites this paper.

Learning to Reason at the Frontier of Learnability Teaching Large Language Models to Reason with Reinforcement Learning

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-23T02:42:26.085841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1a9aa297-dd75-445b-9d9f-0739788963a9 · inbound

Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space cites this paper.

Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space Teaching Large Language Models to Reason with Reinforcement Learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T15:15:43.520186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49fc1608-b320-4489-bbfa-ae4d409b03ac · inbound

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving cites this paper.

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving Teaching Large Language Models to Reason with Reinforcement Learning

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T15:13:43.610133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d19f54ef-db2a-4b5b-867e-f353c9648dd4 · inbound

Think-RM: Enabling Long-Horizon Reasoning in Generative Reward Models cites this paper.

Think-RM: Enabling Long-Horizon Reasoning in Generative Reward Models Teaching Large Language Models to Reason with Reinforcement Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:53.173407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2120d7eb-4477-465d-8dea-891dc5dd9fb2 · inbound

Learning to Select In-Context Demonstration Preferred by Large Language Model cites this paper.

Learning to Select In-Context Demonstration Preferred by Large Language Model Teaching Large Language Models to Reason with Reinforcement Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T14:09:22.127164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b280998b-7aeb-4866-9259-74fd9d347658 · inbound

LoVeC: Reinforcement Learning for Better Verbalized Confidence in Long-Form Generations cites this paper.

LoVeC: Reinforcement Learning for Better Verbalized Confidence in Long-Form Generations Teaching Large Language Models to Reason with Reinforcement Learning

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-19T12:47:17.959953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7e35f750-3716-42a7-88b1-4dbb4526b9d0 · inbound

SCOUT: Teaching Pre-trained Language Models to Enhance Reasoning via Flow Chain-of-Thought cites this paper.

SCOUT: Teaching Pre-trained Language Models to Enhance Reasoning via Flow Chain-of-Thought Teaching Large Language Models to Reason with Reinforcement Learning

Reference 15

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Observation e135594d-1c46-4d77-8a61-9b2fe77ab4d0 · inbound

MoDoMoDo: Multi-Domain Data Mixtures for Multimodal LLM Reinforcement Learning cites this paper.

MoDoMoDo: Multi-Domain Data Mixtures for Multimodal LLM Reinforcement Learning Teaching Large Language Models to Reason with Reinforcement Learning

Reference 17

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Observation a53a291c-66f3-4219-8f0f-dc8fd58cf89f · inbound

Truly Self-Improving Agents Require Intrinsic Metacognitive Learning cites this paper.

Truly Self-Improving Agents Require Intrinsic Metacognitive Learning Teaching Large Language Models to Reason with Reinforcement Learning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T10:28:19.442762Z

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Observation 28fa47da-3602-46cb-bef4-1b7022a8e596 · inbound

RePO: Replay-Enhanced Policy Optimization cites this paper.

RePO: Replay-Enhanced Policy Optimization Teaching Large Language Models to Reason with Reinforcement Learning

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T04:53:56.348495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c3bf2f5-bbaa-4cbe-aa0d-b4f53a75aaf8 · inbound

Intent Factored Generation: Unleashing the Diversity in Your Language Model cites this paper.

Intent Factored Generation: Unleashing the Diversity in Your Language Model Teaching Large Language Models to Reason with Reinforcement Learning

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31b4fc56-00b6-434c-9a07-5a53afa3bab2 · inbound

RAST: Reasoning Activation in LLMs via Small-model Transfer cites this paper.

RAST: Reasoning Activation in LLMs via Small-model Transfer Teaching Large Language Models to Reason with Reinforcement Learning

Reference 16

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Unavailable: canonical work link unavailable.

Observation 30cebf1b-9edf-4c93-a4c6-0d06a81f86d1 · inbound

Learning Efficient Robotic Garment Manipulation with Standardization cites this paper.

Learning Efficient Robotic Garment Manipulation with Standardization Teaching Large Language Models to Reason with Reinforcement Learning

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e441468-f270-49bd-8275-064d1d46a9b2 · inbound

Loki's Dance of Illusions: A Comprehensive Survey of Hallucination in Large Language Models cites this paper.

Loki's Dance of Illusions: A Comprehensive Survey of Hallucination in Large Language Models Teaching Large Language Models to Reason with Reinforcement Learning

Reference 139

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Observation 32d4999e-f949-4bcf-ba50-b84d03b796ca · inbound

When LLMs Copy to Think: Uncovering Copy-Guided Attacks in Reasoning LLMs cites this paper.

When LLMs Copy to Think: Uncovering Copy-Guided Attacks in Reasoning LLMs Teaching Large Language Models to Reason with Reinforcement Learning

Reference 9

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Unavailable: canonical work link unavailable.

Observation 2ee5efad-7c3b-49cb-b87e-062e32774c0e · inbound

Med-R$^3$: Enhancing Medical Retrieval-Augmented Reasoning of LLMs via Progressive Reinforcement Learning cites this paper.

Med-R$^3$: Enhancing Medical Retrieval-Augmented Reasoning of LLMs via Progressive Reinforcement Learning Teaching Large Language Models to Reason with Reinforcement Learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T10:44:26.838066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cccdf65-b86f-4eaa-8584-d24c5534aadb · inbound

RL-PLUS: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy Optimization cites this paper.

RL-PLUS: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy Optimization Teaching Large Language Models to Reason with Reinforcement Learning

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-19T01:16:57.097300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d1ae46cd-7879-4233-b5ff-171a85413323 · inbound

Beyond Memorization: Extending Reasoning Depth with Recurrence, Memory and Test-Time Compute Scaling cites this paper.

Beyond Memorization: Extending Reasoning Depth with Recurrence, Memory and Test-Time Compute Scaling Teaching Large Language Models to Reason with Reinforcement Learning

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-18T20:51:50.809262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7c481f30-7042-4931-9867-16411b6c3d47 · inbound

TaoSR-AGRL: Adaptive Guided Reinforcement Learning Framework for E-commerce Search Relevance cites this paper.

TaoSR-AGRL: Adaptive Guided Reinforcement Learning Framework for E-commerce Search Relevance Teaching Large Language Models to Reason with Reinforcement Learning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T10:53:08.022212Z

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Unavailable: canonical work link unavailable.

Observation 86d251eb-e19e-42fc-aca2-e7b41d675a63 · inbound

CodeRL+: Improving Code Generation via Reinforcement with Execution Semantics Alignment cites this paper.

CodeRL+: Improving Code Generation via Reinforcement with Execution Semantics Alignment Teaching Large Language Models to Reason with Reinforcement Learning

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-18T05:20:54.606098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f7fc2164-4bbc-444f-8172-de9b9d233944 · inbound

Native Parallel Reasoner: Reasoning in Parallelism via Self-Distilled Reinforcement Learning cites this paper.

Native Parallel Reasoner: Reasoning in Parallelism via Self-Distilled Reinforcement Learning Teaching Large Language Models to Reason with Reinforcement Learning

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-17T01:13:47.929498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f81f4d0a-b7c7-4490-9bbc-57456cdccdf8 · inbound

SeLaR: Selective Latent Reasoning in Large Language Models cites this paper.

SeLaR: Selective Latent Reasoning in Large Language Models Teaching Large Language Models to Reason with Reinforcement Learning

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-11T00:35:49.556259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3fa2893a-9d5a-40d5-a0d3-b56879453ce5 · inbound

LiFT: Does Instruction Fine-Tuning Improve In-Context Learning for Longitudinal Modelling by Large Language Models? cites this paper.

LiFT: Does Instruction Fine-Tuning Improve In-Context Learning for Longitudinal Modelling by Large Language Models? Teaching Large Language Models to Reason with Reinforcement Learning

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T00:18:22.899179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6a38efa3-6279-45c4-b446-85466f863fef · inbound

Measure Twice, Click Once: Co-evolving Proposer and Visual Critic via Reinforcement Learning for GUI Grounding cites this paper.

Measure Twice, Click Once: Co-evolving Proposer and Visual Critic via Reinforcement Learning for GUI Grounding Teaching Large Language Models to Reason with Reinforcement Learning

Reference 30

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T14:16:06.034886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 94c2ee82-3972-41d2-9102-f160f9404b65 · inbound

Internalizing Outcome Supervision into Process Supervision: A New Paradigm for Reinforcement Learning for Reasoning cites this paper.

Internalizing Outcome Supervision into Process Supervision: A New Paradigm for Reinforcement Learning for Reasoning Teaching Large Language Models to Reason with Reinforcement Learning

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:26:27.797962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d02a8372-ccfc-427e-8cbc-d60d3256639e · inbound

Logic-Regularized Verifier Elicits Reasoning from LLMs cites this paper.

Logic-Regularized Verifier Elicits Reasoning from LLMs Teaching Large Language Models to Reason with Reinforcement Learning

Reference 72

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T19:51:10.941397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dda6e555-6545-49a4-8474-436f8a5da3d9 · inbound

NoisyCoconut: Counterfactual Consensus via Latent Space Reasoning cites this paper.

NoisyCoconut: Counterfactual Consensus via Latent Space Reasoning Teaching Large Language Models to Reason with Reinforcement Learning

Reference 34

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T08:41:24.258184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d6d976ea-a5e7-40f6-8fe6-1d56bae82ff5 · inbound

Epistemic Uncertainty for Test-Time Discovery cites this paper.

Epistemic Uncertainty for Test-Time Discovery Teaching Large Language Models to Reason with Reinforcement Learning

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:57:06.061818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c81a34d1-d755-4ac4-914f-1d137bb1437d · inbound

When Reasoning Traces Become Performative: Step-Level Evidence that Chain-of-Thought Is an Imperfect Oversight Channel cites this paper.

When Reasoning Traces Become Performative: Step-Level Evidence that Chain-of-Thought Is an Imperfect Oversight Channel Teaching Large Language Models to Reason with Reinforcement Learning

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-13T06:32:24.335451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9a1e33e8-a197-49ed-ae07-e9a23d3c2147 · inbound

From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI cites this paper.

From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI Teaching Large Language Models to Reason with Reinforcement Learning

Reference 139

Resolution: unresolved; no resolver link, observed 2026-08-02T11:29:31.754741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40d461bd-51fb-4411-a91d-074baac150f9 · inbound

Multi-Turn On-Policy Distillation with Prefix Replay cites this paper.

Multi-Turn On-Policy Distillation with Prefix Replay Teaching Large Language Models to Reason with Reinforcement Learning

Reference 44

Resolution: unresolved; no resolver link, observed 2026-07-11T13:53:36.775836Z

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Unavailable: canonical work link unavailable.

Observation 15e17f8c-3d1d-4117-a752-b61ea7913795 · inbound

Multi-Turn On-Policy Distillation with Prefix Replay cites this paper.

Multi-Turn On-Policy Distillation with Prefix Replay Teaching Large Language Models to Reason with Reinforcement Learning

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-02T08:40:36.004785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58f57867-c9d6-4227-84b9-37c8ca272be2 · inbound

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models cites this paper.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Teaching Large Language Models to Reason with Reinforcement Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T13:26:28.373498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3178038-8e0d-482d-b8e8-4a088c93762d · inbound

LeAct: Learning to Reason from Expert Actions cites this paper.

LeAct: Learning to Reason from Expert Actions Teaching Large Language Models to Reason with Reinforcement Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T06:32:19.440448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46f0c937-c1c1-42b7-b42e-7b9169cd431c · inbound

AdaKP: Online Adaptive Knowledge-Point Selection for Reasoning-Oriented Reinforcement Learning cites this paper.

AdaKP: Online Adaptive Knowledge-Point Selection for Reasoning-Oriented Reinforcement Learning Teaching Large Language Models to Reason with Reinforcement Learning

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-01T07:34:56.790463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 639afc79-1014-4fc7-896c-13a2914bd6db · inbound

RepoReasoner: Evaluating Repository-Level Code Reasoning Ability of Long-Context Language Models cites this paper.

RepoReasoner: Evaluating Repository-Level Code Reasoning Ability of Long-Context Language Models Teaching Large Language Models to Reason with Reinforcement Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T00:57:34.320933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b9c5573-8ad2-4bc5-88c1-ea212ae184dc · inbound

Is Inter-Seed Cross-Play Enough? Evaluating the Robustness of Zero-Shot Coordination Algorithms to Implementation Details cites this paper.

Is Inter-Seed Cross-Play Enough? Evaluating the Robustness of Zero-Shot Coordination Algorithms to Implementation Details Teaching Large Language Models to Reason with Reinforcement Learning

Reference 193

Resolution: unresolved; no resolver link, observed 2026-08-05T15:25:40.180493Z

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Unavailable: canonical work link unavailable.