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Paper Citation Record · LEDGER

RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2501.11284.

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

pith.paper-citation-record.v1
2501.11284 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 21 of 21 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 21 of 21 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T00:51:24.917563Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T13:58:21.059264Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0f497445-4ce9-4e84-b302-6c64f19604a5 · inbound

From System 1 to System 2: A Survey of Reasoning Large Language Models cites this paper.

From System 1 to System 2: A Survey of Reasoning Large Language Models RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-05-13T01:36:24.624208Z

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.

source=pdf_text observed=2026-05-13T01:36:23.845366Z digest=sha256:2cd739f2d067685816698cada9c6d6f6be758ff58258ddff4d62449793f45f5e

Observation 258a02af-6a6b-4d99-b955-2268467f3044 · inbound

Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey cites this paper.

Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 234

Resolution
verified exact
arxiv_id, observed 2026-05-15T17:18:53.547307Z

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.

source=pdf_text observed=2026-05-15T17:18:52.996467Z digest=sha256:2b9206f2b249e0af8b49a271675948218cf2903b9e5670229150fdc3ca8432e9

Observation 745326d5-d3df-44cf-8a7b-fc14584ec5d4 · inbound

Large Language Models as Computable Approximations to Solomonoff Induction cites this paper.

Large Language Models as Computable Approximations to Solomonoff Induction RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-07T15:16:57.734912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:16:57.734912Z digest=sha256:349492ec2348bfb6aa5db826e62483d48276d6e08178fd698bcc9d2cdeebc3a8

Observation 51606719-fb28-47d4-ad15-36ff7ef06158 · inbound

STAR-R1: Spatial TrAnsformation Reasoning by Reinforcing Multimodal LLMs cites this paper.

STAR-R1: Spatial TrAnsformation Reasoning by Reinforcing Multimodal LLMs RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-07T15:15:42.262101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:15:42.262101Z digest=sha256:dd2fed3354492d38623ccae5ac26e4b01eb237a6409c333572d16d69e3a4dcbc

Observation e35523a1-55af-462e-9760-58367039a88f · inbound

Activation Control for Efficiently Eliciting Long Chain-of-thought Ability of Language Models cites this paper.

Activation Control for Efficiently Eliciting Long Chain-of-thought Ability of Language Models RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T14:46:13.583355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:46:13.583355Z digest=sha256:a552398d072da2b40706fb32513f158fa504ba6d29e885beaffe10c84b29670f

Observation 6cec24d0-f256-4c17-9cd9-8c44588cd93e · inbound

VisualToolAgent (VisTA): A Reinforcement Learning Framework for Visual Tool Selection cites this paper.

VisualToolAgent (VisTA): A Reinforcement Learning Framework for Visual Tool Selection RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T13:59:39.871961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:59:39.871961Z digest=sha256:aec208f1a584dd193f3805b20aa8994bb088c6daa3e983f280d2305df74e1aad

Observation 7fcb8a4d-1292-4391-ba39-3ac59747cd87 · inbound

Why Distillation can Outperform Zero-RL: The Role of Flexible Reasoning cites this paper.

Why Distillation can Outperform Zero-RL: The Role of Flexible Reasoning RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T13:46:41.856018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:46:41.856018Z digest=sha256:e86f6013173a2a40c2b30ae4ef5ba1c71fcdf59be1a111ab9cc8544019c10de0

Observation f1823873-8f56-4b08-bb8e-2976b786cfea · inbound

More Thinking, Less Seeing? Assessing Amplified Hallucination in Multimodal Reasoning Models cites this paper.

More Thinking, Less Seeing? Assessing Amplified Hallucination in Multimodal Reasoning Models RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T14:51:35.743013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:51:35.743013Z digest=sha256:1d7533dd12585af6d906c012dc87bc7018a8e0414f6e1d89b3b79be9045964d3

Observation db56cecf-9f5a-4d29-9bcf-863d9e379bfa · inbound

One Missing Piece for Open-Source Reasoning Models: A Dataset to Mitigate Cold-Starting Short CoT LLMs in RL cites this paper.

One Missing Piece for Open-Source Reasoning Models: A Dataset to Mitigate Cold-Starting Short CoT LLMs in RL RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T11:30:40.365512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:40.365512Z digest=sha256:be6021e375a50c787d0e155b8ac5a185d21f104510808cb155494e2bea763177

Observation 292b9609-9766-4900-a4d7-9b02281e81cf · inbound

EPiC: Towards Lossless Speedup for Reasoning Training through Edge-Preserving CoT Condensation cites this paper.

EPiC: Towards Lossless Speedup for Reasoning Training through Edge-Preserving CoT Condensation RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T10:52:49.630323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:52:49.630323Z digest=sha256:3b87b5d45f631f30819033bfc60eb2a94d37869e1ae90b0e0a5c14d4f517c2cf

Observation b8cd5682-e691-4445-a0c9-5039ab6d027c · inbound

Logit Arithmetic Elicits Long Reasoning Capabilities Without Training cites this paper.

Logit Arithmetic Elicits Long Reasoning Capabilities Without Training RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T16:46:00.345444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:46:00.345444Z digest=sha256:f5b8ecf97e8d763b1ef0b5f036ab8cdd241c66da9bbdef3c1fb9d3c554441030

Observation b28d8b18-0fdc-4bd4-b0b3-287c237b2b98 · inbound

Can One Domain Help Others? A Data-Centric Study on Multi-Domain Reasoning via Reinforcement Learning cites this paper.

Can One Domain Help Others? A Data-Centric Study on Multi-Domain Reasoning via Reinforcement Learning RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T14:53:04.629639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:53:04.629639Z digest=sha256:e09cd7413afefa46cd1e90d9e662557f98067b6c7be8f51d2cd81abd132c8f19

Observation 1543a353-e86a-4853-b45d-d8927b37cbc1 · inbound

Beyond Solving Math Quiz: Evaluating the Ability of Large Reasoning Models to Ask for Information cites this paper.

Beyond Solving Math Quiz: Evaluating the Ability of Large Reasoning Models to Ask for Information RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-05T20:07:00.485136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T20:07:00.485136Z digest=sha256:ef606feb7a9ce4977ebe5edd34c40a9e389014c61b01bbe097d03bd21c5fa2cd

Observation 3032dd93-6f49-4b75-83cc-bdcb605a58fb · inbound

BudgetThinker: Empowering Budget-aware LLM Reasoning with Control Tokens cites this paper.

BudgetThinker: Empowering Budget-aware LLM Reasoning with Control Tokens RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-05T17:04:38.763726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:04:38.763726Z digest=sha256:3ab70a89a62d070f56c515d05e48091480108b29f027f85d1448398780cf3e9d

Observation 383c04bc-624c-4b91-a06b-d9a1253be304 · inbound

A Comprehensive Survey on Trustworthiness in Reasoning with Large Language Models cites this paper.

A Comprehensive Survey on Trustworthiness in Reasoning with Large Language Models RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-05T10:39:02.106102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:39:02.106102Z digest=sha256:0b02f723fab39e2646ec94b7bc4a873ac2d77a5aa02963c07f93191832eaa37a

Observation 4e616cef-58d9-42c3-bf3d-ef2762e15bda · inbound

ParaThinker: Native Parallel Thinking as a New Paradigm to Scale LLM Test-time Compute cites this paper.

ParaThinker: Native Parallel Thinking as a New Paradigm to Scale LLM Test-time Compute RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-05T13:52:07.032838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:52:07.032838Z digest=sha256:0b4d7a961a77eac33d92ef0421c1c0ae3b3945708e10f553b0bf2c9060725ff3

Observation 68011b37-55ec-4367-a506-ff6573385c05 · inbound

SPM-Bench: Benchmarking Large Language Models for Scanning Probe Microscopy cites this paper.

SPM-Bench: Benchmarking Large Language Models for Scanning Probe Microscopy RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-02T20:36:05.177375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T20:36:05.177375Z digest=sha256:334cd6c4916da1d398f2d95faade4ed0c7a522d9932dd9d417e45b4926148e6b

Observation 08070b7a-8ea2-4972-bcdd-cd9f20195fa3 · inbound

Uni-OPD: Unifying On-Policy Distillation with a Dual-Perspective Recipe cites this paper.

Uni-OPD: Unifying On-Policy Distillation with a Dual-Perspective Recipe RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:26:15.869637Z

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.

source=pdf_text observed=2026-05-07T17:00:49.448352Z digest=sha256:b9d35a7e04d562d12d7fa63b69c6ff098344b09f4ed8b57345a4b1217d16d114

Observation cc5f5136-6512-40a9-bf8e-4bc81879f62b · inbound

IS-CoT: Breaking the Long-form Generation Collapse via Interleaved Structural Thinking cites this paper.

IS-CoT: Breaking the Long-form Generation Collapse via Interleaved Structural Thinking RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 40

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T01:37:30.879462Z

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.

source=arxiv_source observed=2026-06-27T16:25:57.418334Z digest=sha256:5fb56133885050ae5633e0c6feff612886d24ecc8fa2864df08477376ca4b480

Observation 27423c9b-7915-46d9-9a73-c223ed073c6a · inbound

Purified OPSD: On-Policy Self-Distillation Without Losing How to Think cites this paper.

Purified OPSD: On-Policy Self-Distillation Without Losing How to Think RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-07-03T13:58:21.060965Z

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.

source=pdf_text observed=2026-07-03T13:56:13.827493Z digest=sha256:b9e10e5db6e34c01c81bf4c7e2ddd718188023bbb64ca675448fe9b3479f7e38

Observation feda317e-f4f1-4c84-b724-c765eae22b4d · inbound

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs cites this paper.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-08T00:51:24.917563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.917563Z digest=sha256:b6e0e30596508637d76248e2e3c6690d148ce880fca9090b34530884cd0ad814