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Paper Citation Record · LEDGER

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models

As of 22 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 3 inbound Pith citation observations for arXiv:2506.04182.

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

pith.paper-citation-record.v1
2506.04182 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:52:45.240631Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:30:44.884054Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:54:18.778705Z

Reference resolution

35 of 35 outbound references displayed

  • verified exact0
  • verified fuzzy9
  • unresolved26
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3e02eb7e-a277-42cc-87da-44fdc81f5f81 · outbound

This paper cites Aime 2025 dataset.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Aime 2025 dataset

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:52:47.837113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T10:52:42.751765Z digest=sha256:aeb1d96ba038829a458a4750d10b8232134684ed7cd58732aece942959608eea

Observation e488b7b9-dc7f-4897-9369-59cfb4d22970 · outbound

This paper cites Amc 2023 dataset, 2023.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Amc 2023 dataset, 2023

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-07T10:52:47.640397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T10:52:42.819271Z digest=sha256:4b944532f6f433aff2f66d1d6f6f83346fd320123ad85aba0e0ede1045831027

Observation ea58a8b9-205e-4ddc-af18-6ec0deec0a09 · outbound

This paper cites Training language models to reason efficiently, 2025.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Training language models to reason efficiently, 2025

Reference 3

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no resolver link, observed 2026-08-07T10:52:42.890260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:42.890260Z digest=sha256:1bb0e1d4c09f58144aee1d660105c1d45c540e1ff8680fa5c7cb45db1885e2cc

Observation b45e00b3-0d8b-415b-970b-6d95091dc51d · outbound

This paper cites Graph of thoughts: Solving elaborate problems with large language models.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Graph of thoughts: Solving elaborate problems with large language models

Reference 4

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no resolver link, observed 2026-08-07T10:52:42.958567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:42.958567Z digest=sha256:866fdf1114ec80f5702abd77dcb6e86dce89bbe7169152a87f2410f30f79efd1

Observation 12015bbf-0e73-4422-aea3-09288d883f9f · outbound

This paper cites Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs

Reference 5

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no resolver link, observed 2026-08-07T10:52:43.032330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:43.032330Z digest=sha256:c9349fe2a6319ddbbfdab6f1f3694c83cff5d181062728bdc46462ff38cf5298

Observation b320e41c-677f-4b64-8571-9ad504432ac1 · outbound

This paper cites Compressed Chain of Thought: Efficient Reasoning Through Dense Representations.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Compressed Chain of Thought: Efficient Reasoning Through Dense Representations

Reference 6

Resolution
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no resolver link, observed 2026-08-07T10:52:43.087566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:43.087566Z digest=sha256:3e2165a01c55e63a3819b55efb65e49c3f9dbaa10924256938ae9cc2b8a9f553

Observation 2f78083d-ee61-4867-b636-883911241b4d · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 7

Resolution
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no resolver link, observed 2026-08-07T10:52:43.135020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:43.135020Z digest=sha256:0f4e6279c8b3995104ad1552e94ea2dc31d748d0b3ab99d2fc7be2e4038b31fe

Observation 9d94840a-fcf3-4179-9096-3bf28f37995e · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Training Verifiers to Solve Math Word Problems

Reference 8

Resolution
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no resolver link, observed 2026-08-07T10:52:43.197117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:43.197117Z digest=sha256:0de046a29ff5d2c07e528319912b8e6298f8f815e22c6c0cd55e29545d5426c1

Observation 590ffeab-1d10-41f9-b184-c2adb6beb9c9 · outbound

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

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 9

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no resolver link, observed 2026-08-07T10:52:43.262363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:43.262363Z digest=sha256:8a0ed2c19d38edcaf738157d7eccd188082fca7ccbc651686c9725effd65ecce

Observation 3df8f4b6-63c7-4f29-b1ee-db42314184ab · outbound

This paper cites Token-Budget-Aware LLM Reasoning.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Token-Budget-Aware LLM Reasoning

Reference 10

Resolution
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no resolver link, observed 2026-08-07T10:52:43.358336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:43.358336Z digest=sha256:04eb7c520cee499fd2051af4fdabf2ee534b39372277507ab16c430c193a7769

Observation e6dab186-6114-4532-b844-dd85a44fa5c9 · outbound

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

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Training Large Language Models to Reason in a Continuous Latent Space

Reference 11

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no resolver link, observed 2026-08-07T10:52:43.426385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:43.426385Z digest=sha256:18a7cbe58e3cc6debfb773a6f4d092112679d0c2cc0c19651c085b8d7e0fec49

Observation b104004b-8362-4a70-98e4-9968f0c770b9 · outbound

This paper cites Measuring massive multitask language understanding.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Measuring massive multitask language understanding

Reference 12

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no resolver link, observed 2026-08-07T10:52:43.499941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:43.499941Z digest=sha256:f36ea20f02dfacc07f1b03f3005589a7d7ccc317fb819a5a8108a87e104d2ca5

Observation 24d68348-f322-4e3b-af59-53b5ea542bf5 · outbound

This paper cites How Well do LLMs Compress Their Own Chain-of-Thought? A Token Complexity Approach.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models How Well do LLMs Compress Their Own Chain-of-Thought? A Token Complexity Approach

Reference 13

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no resolver link, observed 2026-08-07T10:52:43.571421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:43.571421Z digest=sha256:d92793021c9c72bbf22f81394f50d7a17e7cdeb30daf9eb95661268eca8529b8

Observation d96fd685-82f7-41db-9b93-0e66ce407fc1 · outbound

This paper cites Let's Verify Step by Step.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Let's Verify Step by Step

Reference 14

Resolution
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no resolver link, observed 2026-08-07T10:52:43.642199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:43.642199Z digest=sha256:8f976d9989fab70561603b36869623aebf70b5466b9b39804400ac66440339bc

Observation 9acbe5aa-4f54-4fa6-a216-c3ac9d1bc68c · outbound

This paper cites Can Language Models Learn to Skip Steps?.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Can Language Models Learn to Skip Steps?

Reference 15

Resolution
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no resolver link, observed 2026-08-07T10:52:43.731124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:43.731124Z digest=sha256:31164011b9d7961703ca50044d68bcc0003651180c3b6a127b92558d9f72adbd

Observation eb316e4b-aed5-4634-a520-c972fbdd79bb · outbound

This paper cites Thought Manipulation: External Thought Can Be Efficient for Large Reasoning Models.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Thought Manipulation: External Thought Can Be Efficient for Large Reasoning Models

Reference 16

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no resolver link, observed 2026-08-07T10:52:43.812067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:43.812067Z digest=sha256:d12cad92bd4bae1f1aef2f88fd067593584ee6bab1b0a11ba30e43cf51979565

Observation f961489e-3869-4784-af32-f8d33b56c7e9 · outbound

This paper cites Reasoning models can be effective without thinking.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Reasoning models can be effective without thinking

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:52:47.429279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T10:52:43.863165Z digest=sha256:c7b144d2aef2cab8ea461ebe9133cc892b4951227eaaa8f87029e50884106d4e

Observation 7da4ff0c-8659-4c4e-980a-40cfeea82993 · outbound

This paper cites Reasoning Models Can Be Effective Without Thinking.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Reasoning Models Can Be Effective Without Thinking

Reference 18

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no resolver link, observed 2026-08-07T10:52:43.931777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:43.931777Z digest=sha256:fc3d27ea8ee6965a2da54f01fde6ca5e654dcbe2f4cdb65199c851e5c048f2ce

Observation 5051bc73-093d-423f-bee0-ad47df6de5d2 · outbound

This paper cites s1: Simple test-time scaling.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models s1: Simple test-time scaling

Reference 19

Resolution
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no resolver link, observed 2026-08-07T10:52:44.016695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:44.016695Z digest=sha256:fa45e73185abad90236a3afe54491cc4f2c990b960d07afb88a9000527a256b3

Observation c45e0a8a-2373-4eea-bacd-08e286482b93 · outbound

This paper cites Learning to reason with llms., 2024.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Learning to reason with llms., 2024

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:52:47.156985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T10:52:44.071438Z digest=sha256:798cce94c78f4e3ce35df31dcae458b8c5c9a4ff8555cf83b52569e41d371cf4

Observation 0643ee1f-2868-48f9-9b64-e671a506c77a · outbound

This paper cites Opentriviaqa dataset, 2020.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Opentriviaqa dataset, 2020

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:52:46.911299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T10:52:44.129012Z digest=sha256:0d75e9c085617f5088c11a796cd2b8f27b233b16bcf996b1f0fe1a44ca43b73d

Observation 2556b288-b3bb-4743-95fa-7971d878751b · outbound

This paper cites poetry dataset, 2024.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models poetry dataset, 2024

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:52:46.596847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T10:52:44.161132Z digest=sha256:6849568a6ea397a540ed706c4867337d86a967315089f1f0a087c4d1b434d5d3

Observation 51ae1475-2fbf-4c95-9ffc-d479ee3d1d84 · outbound

This paper cites Qwen3: Think deeper, act faster, 2025.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Qwen3: Think deeper, act faster, 2025

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:52:46.263452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T10:52:44.224956Z digest=sha256:1ca6b1ba962860211b155818fb4bad8dd003e51d32e2e187643e0f20ce77a860

Observation 931b8e21-369d-4411-a005-04199fbecf20 · outbound

This paper cites Gpqa: A graduate-level google-proof q&a benchmark.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Gpqa: A graduate-level google-proof q&a benchmark

Reference 24

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no resolver link, observed 2026-08-07T10:52:44.295130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:44.295130Z digest=sha256:3762f5a60a8e2cd029b0180a3ae72036cf4aa3a6a2c91f93e1108c72d64caadc

Observation 88d772ed-4336-45de-83d2-0931fbdc0adc · outbound

This paper cites The benefits of a concise chain of thought on problem-solving in large language models.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models The benefits of a concise chain of thought on problem-solving in large language models

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:52:46.001285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T10:52:44.381173Z digest=sha256:b46ade89d1c98dc362e107d2c4e2f3231b7478d0d677376a15ac5a25d97adedd

Observation 49922946-a9e6-479f-9e12-5d4c2b699866 · outbound

This paper cites SocialIQA: Commonsense Reasoning about Social Interactions.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models SocialIQA: Commonsense Reasoning about Social Interactions

Reference 26

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no resolver link, observed 2026-08-07T10:52:44.456211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:44.456211Z digest=sha256:7884bd5051d9aba48cc6333b1b61162c166b686327e7656843e04743b07dfe2a

Observation b348cb13-9d30-4f07-8795-e65cfa790a12 · outbound

This paper cites Manning, Andrew Ng, and Christopher Potts.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Manning, Andrew Ng, and Christopher Potts

Reference 27

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unresolved
no resolver link, observed 2026-08-07T10:52:44.546182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:44.546182Z digest=sha256:fa6c011103606e286f5826cd1ba76c679e832286633c0efab208887152a7cb3c

Observation 99377462-f1da-40c6-89b0-ba634be91df5 · outbound

This paper cites Brown, Adam Santoro, Aditya Gupta, Adri \`a Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Brown, Adam Santoro, Aditya Gupta, Adri \`a Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-07T10:52:45.793676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-07T10:52:44.672515Z digest=sha256:675269d566572f18f52cc7f5f3deb4f02fc7ae9dc9fa86808434621cd92dbb68

Observation dd3660a6-87d6-4a84-9189-cf6483b32d49 · outbound

This paper cites Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T10:52:44.759130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:44.759130Z digest=sha256:0097bc706ad9e83f864743cbd1550647bf8ab28441eae21977192d10bea25ff4

Observation 43725162-fbc6-4ba3-b3fa-e03f61513162 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Chain-of-thought prompting elicits reasoning in large language models

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T10:52:44.850130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:44.850130Z digest=sha256:fcf3926f160174e63994b5955326ab65d0dd6359a5c41fdfb2f501e086cba90a

Observation 32e79d90-fd70-4a7e-aa2f-415848bd3664 · outbound

This paper cites When More is Less: Understanding Chain-of-Thought Length in LLMs.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models When More is Less: Understanding Chain-of-Thought Length in LLMs

Reference 31

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unresolved
no resolver link, observed 2026-08-07T10:52:44.856609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:44.856609Z digest=sha256:5743badec9cfbdfb2cc5e24ae0096211f29f0e4870e7d80b59b83648cba2d254

Observation 4071d878-1ec9-438b-8666-f8d86b6df9e6 · outbound

This paper cites Tokenskip: Controllable chain-of-thought compression in llms.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Tokenskip: Controllable chain-of-thought compression in llms

Reference 32

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unresolved
no resolver link, observed 2026-08-07T10:52:44.947071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:44.947071Z digest=sha256:f9ebffdf2c4249b71132823ec12a582c49e83a2c86990e12e88f2d6b1fdb0c8e

Observation 686d7cf5-c0e8-423d-8cd4-32940ec21008 · outbound

This paper cites Chain of Draft: Thinking Faster by Writing Less.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Chain of Draft: Thinking Faster by Writing Less

Reference 33

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no resolver link, observed 2026-08-07T10:52:45.010899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:45.010899Z digest=sha256:28d996b05811552e0b3c638ee47bbee761681de91ea21bb3dae1882651f88fb2

Observation 7ca7a04e-cd08-407b-96fa-eddcacfaaccf · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models Tree of thoughts: Deliberate problem solving with large language models

Reference 34

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no resolver link, observed 2026-08-07T10:52:45.114159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:45.114159Z digest=sha256:45178d1fb179bf54af38bcbaa77f1c92e93b656047638dca4008335508706fab

Observation 581f2270-aeb8-4e76-b25a-9e9b07e4afc5 · outbound

This paper cites write newline.

Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models write newline

Reference 35

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unresolved
no resolver link, observed 2026-08-07T10:52:45.240631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:45.240631Z digest=sha256:77db176ac125af11742b682475f5a69c8aab79b152d8e906581d5100f2118948

Pith citing papers

Observation a098fc77-5446-40ee-8841-4e52fbd8b644 · inbound

Strategic Reflectivism In Intelligent Systems cites this paper.

Strategic Reflectivism In Intelligent Systems Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models

Reference 85

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no resolver link, observed 2026-08-07T12:59:26.792078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:59:26.792078Z digest=sha256:43f1161d947f92026f237ca81715b57481c91365a3b866debe716c01df48dab7

Observation ec93ce0d-dc94-4c2e-82d4-d52b37244f37 · 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 Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models

Reference 242

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:54:18.783995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T17:54:18.079107Z digest=sha256:e775f0d875e32e534c5b22aeb8add50084a3e51de7504eae973c7fae1d367784

Observation 4d2c07b8-e5b0-4679-a03c-d0ef07c996a0 · inbound

Beyond Correctness: Benchmarking and Aligning Response Behaviors in Hybrid-Thinking MLLMs cites this paper.

Beyond Correctness: Benchmarking and Aligning Response Behaviors in Hybrid-Thinking MLLMs Long or short CoT? Investigating Instance-level Switch of Large Reasoning Models

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-15T23:30:44.884054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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