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Paper Citation Record · LEDGER

The Impact of Reasoning Step Length on Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2401.04925.

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

pith.paper-citation-record.v1
2401.04925 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 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 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:55:24.723010Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T22:06:16.140793Z

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 f39bf3b6-f4ac-47a1-9951-e34d974c74af · 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 The Impact of Reasoning Step Length on Large Language Models

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-13T01:36:24.593530Z

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=pdf_text observed=2026-05-13T01:36:23.845366Z digest=sha256:581e6620c41616c8c5bd945b2e5f926854ee0c5f65a1aa253c316b3c6019ed70

Observation e000c368-a752-430a-bbb8-9b4f1685e435 · inbound

Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models cites this paper.

Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models The Impact of Reasoning Step Length on Large Language Models

Reference 76

Resolution
verified exact
arxiv_id, observed 2026-05-14T01:29:56.755718Z

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=pdf_text observed=2026-05-14T01:29:56.480020Z digest=sha256:81d4e7c86ee0abc2678c8828e5b92f44d45ff078518397ed33ce1797be6de1f3

Observation 7a35277b-64d7-4fe1-9989-236a8777101d · inbound

ARB: A Comprehensive Arabic Multimodal Reasoning Benchmark cites this paper.

ARB: A Comprehensive Arabic Multimodal Reasoning Benchmark The Impact of Reasoning Step Length on Large Language Models

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T14:55:24.723010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:55:24.723010Z digest=sha256:8d07bcc825b43ee40364ebb3ab4ef68f00512ec7af5e992892a73ee4d538b9c7

Observation 9b5d2bbe-8e6a-4cff-85f2-8db749303448 · inbound

Enhancing LLMs' Reasoning-Intensive Multimedia Search Capabilities through Fine-Tuning and Reinforcement Learning cites this paper.

Enhancing LLMs' Reasoning-Intensive Multimedia Search Capabilities through Fine-Tuning and Reinforcement Learning The Impact of Reasoning Step Length on Large Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T14:27:49.887553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:27:49.887553Z digest=sha256:08a98075415e828e9fb25a7866334b2d427a8dba14cae64e6335ff7fc1b416a8

Observation b9bb9319-88cc-4637-8039-8780c4cb8c56 · inbound

Reasoning Can Hurt the Inductive Abilities of Large Language Models cites this paper.

Reasoning Can Hurt the Inductive Abilities of Large Language Models The Impact of Reasoning Step Length on Large Language Models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T12:36:16.046121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:36:16.046121Z digest=sha256:615be740acd389f6f32c8602d55d7c29b1a3a77b91dc5e2296d29c26c3a7ad68

Observation 3dcc2852-3a6e-49bf-82cc-ffd3dcd0bcc4 · inbound

Cell-o1: Training LLMs to Solve Single-Cell Reasoning Puzzles with Reinforcement Learning cites this paper.

Cell-o1: Training LLMs to Solve Single-Cell Reasoning Puzzles with Reinforcement Learning The Impact of Reasoning Step Length on Large Language Models

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T11:16:59.137930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:16:59.137930Z digest=sha256:c7ffc26cc7c425198fdc934137e7f8caf86162b30d717aa3abb1a44ae5edbc8b

Observation 92df2013-73cf-49b2-9f3d-d74aea305a97 · inbound

Reasoning or Overthinking: Evaluating Large Language Models on Financial Sentiment Analysis cites this paper.

Reasoning or Overthinking: Evaluating Large Language Models on Financial Sentiment Analysis The Impact of Reasoning Step Length on Large Language Models

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T10:42:54.722718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:42:54.722718Z digest=sha256:7c33b63b43a376209240c1472c92407c94e334e94ef69ae2e631f86ba61dc590

Observation f08d32ef-1eaf-4d0c-8735-f98ab106f7d1 · inbound

Overclocking LLM Reasoning: Monitoring and Controlling Thinking Path Lengths in LLMs cites this paper.

Overclocking LLM Reasoning: Monitoring and Controlling Thinking Path Lengths in LLMs The Impact of Reasoning Step Length on Large Language Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T05:45:05.901186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:45:05.901186Z digest=sha256:127aee03479e9b64c78b42a9b7faba4069cf2fd7dae4a463f7bd99645c7978cb

Observation 3750dc38-2bfd-4a39-a36a-020960dc4387 · inbound

ReCUT: Balancing Reasoning Length and Accuracy in LLMs via Stepwise Trails and Preference Optimization cites this paper.

ReCUT: Balancing Reasoning Length and Accuracy in LLMs via Stepwise Trails and Preference Optimization The Impact of Reasoning Step Length on Large Language Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T04:24:02.102954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:24:02.102954Z digest=sha256:d80fa2e1068ef0df71da57aeaf4eb73f88b386de049783adb86cb5765f421289

Observation a645a67e-703c-4677-90bd-4304def4d914 · inbound

Intelligent Assistants for the Semiconductor Failure Analysis with LLM-Based Planning Agents cites this paper.

Intelligent Assistants for the Semiconductor Failure Analysis with LLM-Based Planning Agents The Impact of Reasoning Step Length on Large Language Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T23:56:29.986682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:56:29.986682Z digest=sha256:8c7ff87e8cbf9f6feec5aceabc53c39479d878cb9c7387ba9632938071eef4db

Observation 6cb25bc9-63f5-4393-a4bc-dee21072b0d2 · inbound

Test-Time Scaling with Reflective Generative Model cites this paper.

Test-Time Scaling with Reflective Generative Model The Impact of Reasoning Step Length on Large Language Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T20:46:44.770899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:46:44.770899Z digest=sha256:657c203f7c75982ffc53b97a8257b248d9940f6989d9c7e9f3929cbd88c5b101

Observation 73e17fc6-e8b1-41cd-9360-889355df89ce · inbound

Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey cites this paper.

Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey The Impact of Reasoning Step Length on Large Language Models

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-06T17:54:16.725850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:54:16.725850Z digest=sha256:90dafc42ed024d2936668775400d2a5349d0d7ab34396cdd784b22fa53c261a8

Observation b85ca0c7-8270-46df-aa62-eeeaeeac55b6 · inbound

R2-Router: A New Paradigm for LLM Routing with Reasoning cites this paper.

R2-Router: A New Paradigm for LLM Routing with Reasoning The Impact of Reasoning Step Length on Large Language Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-03T05:17:29.854230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:17:29.854230Z digest=sha256:bf687c4ee9a860bbad42186f4b64c6804367a78b6b0f8057f6656b126b869851

Observation ad883f42-7a76-42b3-b2f1-7cd75d8952c4 · inbound

Post Reasoning: Improving the Performance of Non-Thinking Models at No Cost cites this paper.

Post Reasoning: Improving the Performance of Non-Thinking Models at No Cost The Impact of Reasoning Step Length on Large Language Models

Reference 174

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T20:06:09.748170Z

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=2026-05-08T10:19:08.451445Z digest=sha256:18763758bdac6c45c86a3967659eefac97e03bdd043af41157e5821e881adc78

Observation 2b2e4778-f1ff-4a94-b746-e85bd693dab9 · inbound

Rethinking the Role of Positional Encoding: Sliding-Window Transformers without PE Remain Turing Complete cites this paper.

Rethinking the Role of Positional Encoding: Sliding-Window Transformers without PE Remain Turing Complete The Impact of Reasoning Step Length on Large Language Models

Reference 21

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T22:06:16.143480Z

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=2026-06-28T15:48:48.046003Z digest=sha256:20c833326e6653f86ac376960adb2ebb61817b369c9b17309bbdb7e7fe31fad8