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Paper Citation Record · LEDGER

The Impact of Reasoning Step Length on Large Language Models

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 32 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 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 32 of 32 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:02:43.174147Z

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

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3e082394-610d-437c-b61f-eed8904a0b7b · inbound

Reducing Reasoning Costs: The Path of Optimization for Chain of Thought via Sparse Attention Mechanism cites this paper.

Reducing Reasoning Costs: The Path of Optimization for Chain of Thought via Sparse Attention Mechanism The Impact of Reasoning Step Length on Large Language Models

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T21:07:14.067573Z digest=sha256:55d352b0e15edbd106a362198e2f6ad063941df0a34250c99c9926897cb9c114

Observation 1ac934fb-3d04-40f6-91a5-53573afec9ee · inbound

PSPO*: An Effective Process-supervised Policy Optimization for Reasoning Alignment cites this paper.

PSPO*: An Effective Process-supervised Policy Optimization for Reasoning Alignment The Impact of Reasoning Step Length on Large Language Models

Reference 10

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source=arxiv_source observed=2026-08-12T18:20:13.912332Z digest=sha256:705c5056252bacc9a5aaa1560fc3d0949213cd63852b42b0bbd6c6f5a122633a

Observation 0a7934fd-cbe2-4a51-9c7d-ac657e7c43b0 · inbound

Chain-of-Thought in Large Language Models: Decoding, Projection, and Activation cites this paper.

Chain-of-Thought in Large Language Models: Decoding, Projection, and Activation The Impact of Reasoning Step Length on Large Language Models

Reference 14

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source=arxiv_source observed=2026-08-11T21:59:01.351487Z digest=sha256:97be9823014725ccfd709d28dff6105e8d4fba5d3ef4356f65b9b1f70a6179ab

Observation 42669fb0-66f8-4957-b239-7eabd02b3fa1 · inbound

Steps are all you need: Rethinking STEM Education with Prompt Engineering cites this paper.

Steps are all you need: Rethinking STEM Education with Prompt Engineering The Impact of Reasoning Step Length on Large Language Models

Reference 12

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no resolver link, observed 2026-08-11T21:05:20.565149Z

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source=pdf_text observed=2026-08-11T21:05:20.565149Z digest=sha256:d0fbeca5c6284ccfe69df57e935966073347b20abf82b12c7fc795fee4a99fb3

Observation 9a09853e-506e-472a-aa46-415aa446580b · inbound

C3oT: Generating Shorter Chain-of-Thought without Compromising Effectiveness cites this paper.

C3oT: Generating Shorter Chain-of-Thought without Compromising Effectiveness The Impact of Reasoning Step Length on Large Language Models

Reference 20

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source=arxiv_source observed=2026-08-11T14:47:03.901304Z digest=sha256:7b013f71dacff7185a55ccd0c83cef57af07ff1651d28a0126e34b4f7cf7f677

Observation 7d37e4fe-4860-4420-90d2-9b35f06f2d5f · inbound

System-2 Mathematical Reasoning via Enriched Instruction Tuning cites this paper.

System-2 Mathematical Reasoning via Enriched Instruction Tuning The Impact of Reasoning Step Length on Large Language Models

Reference 22

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:58:55.036537Z digest=sha256:14bb91b57926fd9c5247bc7ba2022438a8018c607d95d3e9befbdc6f53bf1318

Observation 6f076219-987c-4305-ba27-3bbc45385cb6 · inbound

CDS: Knowledge Component-Driven Data Synthesis Guided by Cognitive Diagnosis Theory cites this paper.

CDS: Knowledge Component-Driven Data Synthesis Guided by Cognitive Diagnosis Theory The Impact of Reasoning Step Length on Large Language Models

Reference 24

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source=arxiv_source observed=2026-08-10T20:44:16.935801Z digest=sha256:6078af18f76e7762640315e19f016b4e2bacd3c8a8f259774faa4460c8a3dd1e

Observation 6e9b65b5-40ce-4d6e-bbf6-3c801369c065 · inbound

Code Benchmarks Should Prioritize Rigor, Reliability, and Reproducibility cites this paper.

Code Benchmarks Should Prioritize Rigor, Reliability, and Reproducibility The Impact of Reasoning Step Length on Large Language Models

Reference 1442

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source=pdf_text observed=2026-08-10T19:04:25.931274Z digest=sha256:44652b3adbb4105ceb160b7db676f71eb9a579cb7fc632c5d55cd8b976db3549

Observation 09901895-e362-4a53-adb2-f87bde17d455 · inbound

Dynamic Chain-of-Thought: Towards Adaptive Deep Reasoning cites this paper.

Dynamic Chain-of-Thought: Towards Adaptive Deep Reasoning The Impact of Reasoning Step Length on Large Language Models

Reference 9

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source=pdf_text observed=2026-08-08T20:51:16.689289Z digest=sha256:b8532a3a3b96ef15f09d0d90530a11ca9aec5acdad494e25d8666c243db01963

Observation 5f2c60d2-4434-494c-a269-c1774d48298a · inbound

Level-Navi Agent: A Framework and benchmark for Chinese Web Search Agents cites this paper.

Level-Navi Agent: A Framework and benchmark for Chinese Web Search Agents The Impact of Reasoning Step Length on Large Language Models

Reference 7

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:17:48.446019Z digest=sha256:6438fe80330583b3e6a1ccc744f2eacefaa7df77116b9e305c54c9d49e8f450c

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

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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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-13T01:36:23.845366Z digest=sha256:b7a4f6806057ae0c6a844b53953790add77b86207aa8800a3705ade375e5e56e

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

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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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-14T01:29:56.480020Z digest=sha256:c00abdff17955db82b0a2f59cc20a99c01d6eae51d1c3823598640a6df22bef5

Observation 9b7fc6de-5741-40cb-88a3-afe9374e881b · inbound

Generative AI Act II: Test Time Scaling Drives Cognition Engineering cites this paper.

Generative AI Act II: Test Time Scaling Drives Cognition Engineering The Impact of Reasoning Step Length on Large Language Models

Reference 143

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:02:43.174147Z digest=sha256:a80eae4a8e8a29c4bf02e4804ba40468c2f872a622a7a9025068ecca62ca5e1d

Observation 5bd32e47-650f-4abb-a968-448afe3fc545 · inbound

SplitReason: Learning To Offload Reasoning cites this paper.

SplitReason: Learning To Offload Reasoning The Impact of Reasoning Step Length on Large Language Models

Reference 5

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source=pdf_text observed=2026-08-16T11:10:15.302651Z digest=sha256:a95a4cfd8fb87e737568f0ade119e8a05b8d1f0af74c29a850f9ccc54c9de89b

Observation 71d6e80b-55a2-4caa-89bd-775efcae40a3 · inbound

Between Underthinking and Overthinking: An Empirical Study of Reasoning Length and correctness in LLMs cites this paper.

Between Underthinking and Overthinking: An Empirical Study of Reasoning Length and correctness in LLMs The Impact of Reasoning Step Length on Large Language Models

Reference 11

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source=pdf_text observed=2026-08-16T04:55:02.773200Z digest=sha256:a7c14dded803886c3660d89a5d064b1af6afb1adb6141f60675472d64048acd9

Observation 2a969319-8f2c-4325-9f57-8bbdac892614 · inbound

Not All Thoughts are Generated Equal: Efficient LLM Reasoning via Multi-Turn Reinforcement Learning cites this paper.

Not All Thoughts are Generated Equal: Efficient LLM Reasoning via Multi-Turn Reinforcement Learning The Impact of Reasoning Step Length on Large Language Models

Reference 9

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no resolver link, observed 2026-08-15T20:52:27.664401Z

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source=pdf_text observed=2026-08-15T20:52:27.664401Z digest=sha256:5673be4e1019c3bf00164476a78abfae814727b466fa90b437f31956d7f8fb54

Observation c8bfe22a-26d3-4d09-a77b-4fa1030fd3f5 · inbound

RBF++: Quantifying and Optimizing Reasoning Boundaries across Measurable and Unmeasurable Capabilities for Chain-of-Thought Reasoning cites this paper.

RBF++: Quantifying and Optimizing Reasoning Boundaries across Measurable and Unmeasurable Capabilities for Chain-of-Thought Reasoning The Impact of Reasoning Step Length on Large Language Models

Reference 34

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no resolver link, observed 2026-08-15T20:21:21.430667Z

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source=pdf_text observed=2026-08-15T20:21:21.430667Z digest=sha256:6c77d5d52f542f50974fba609bbd1eb12350b96b1a0e8c445dad3c4a6c367f0c

Observation 86972091-2c53-47a7-b7de-4f1e2bc0db7b · inbound

CoIn: Counting the Invisible Reasoning Tokens in Commercial Opaque LLM APIs cites this paper.

CoIn: Counting the Invisible Reasoning Tokens in Commercial Opaque LLM APIs The Impact of Reasoning Step Length on Large Language Models

Reference 11

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no resolver link, observed 2026-08-15T20:15:53.725373Z

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source=arxiv_source observed=2026-08-15T20:15:53.725373Z digest=sha256:ec6eb7b75791d951617155a55fe2393479e92ba3263b98fcef4c6c21f0021706

Observation f3fa983d-3fd1-4f6a-b574-b59d37bb6bd8 · inbound

Structured Agent Distillation for Large Language Model cites this paper.

Structured Agent Distillation for Large Language Model The Impact of Reasoning Step Length on Large Language Models

Reference 17

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source=pdf_text observed=2026-08-15T20:16:19.444720Z digest=sha256:c1626f00d5000742f3a70e7b5f6605ac62cc825e457e071e43049dad41e9335b

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

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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=sha256:41418c13aa0e5ae98901d27718603e67f85fc239416b4841492c8c7b10a41b82

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

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:27:49.887553Z digest=sha256:f051f3fe05fc1eb02136a79687ff6dda6471e261144a0a1fc0d44bac79388cb7

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

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

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source=pdf_text observed=2026-08-07T12:36:16.046121Z digest=sha256:ed25e36934520ebb7c74dc55028d30991f1b3290858699929acd648fa7924432

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

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source=pdf_text observed=2026-08-07T11:16:59.137930Z digest=sha256:4a8ceada10ee2d61e54934879683d11737e72d085b9f196391c9288d34fac747

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

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

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source=pdf_text observed=2026-08-07T10:42:54.722718Z digest=sha256:3f58a3d20fbaed141777cd7bcd8c0a32095d80b5a1b17e0b72b6a62e3ce2c516

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

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

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source=pdf_text observed=2026-08-07T05:45:05.901186Z digest=sha256:3dc1e3edb22e8b0366e40037dff203aa2c0c42032f2b78319c668134608a675d

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

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source=arxiv_source observed=2026-08-07T04:24:02.102954Z digest=sha256:4516d3a68b64d89195db69702454ed68c6478cea07210369d7a310c655ef4e40

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

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

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source=pdf_text observed=2026-08-06T23:56:29.986682Z digest=sha256:7799ec20713c9285cff0015713a72b830ba4cdab8c469348cc3e015c0870000e

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

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source=pdf_text observed=2026-08-06T20:46:44.770899Z digest=sha256:a57c4a8d8034add8048dea1a6371fc767e48382d7b934f2a4879ff00888b837f

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

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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:54:16.725850Z digest=sha256:d105a969aa9c0169496b1b8aeb5ec397127a1b879ca5e5218ff517b7aab21282

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

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source=pdf_text observed=2026-08-03T05:17:29.854230Z digest=sha256:2cef5c535e471db9012e56114cac7fe03798584f759abd9e39a6d6cd79d5f370

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

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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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-08T10:19:08.451445Z digest=sha256:e84479e9d388770fcb425efe15ca98d4ecab86ab708ef0e71c535e3ef59ff761

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

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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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-28T15:48:48.046003Z digest=sha256:4fd808e0c41f0d33d6e804c7d02ae7274131dd64ebdaddcede80def46dfabf9e