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Paper Citation Record · LEDGER

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

As of 7 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 2 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 37 of 37 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:59:26.792078Z

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:52:42.751765Z digest=sha256:3ed070bf16ed2c3a23d1d84463b64b0cda95a4084d12058c45a1e8dad139004d

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:52:42.819271Z digest=sha256:8343a09a42f4468fe10200c5ea78680402e595cd87cc1036129bcce41733c81d

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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unresolved
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:be36570d0c4361e65961161df75734076e224f3cd70fc3734fb3a9c3d9438b3d

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

Resolution
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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=sha256:1a82dd908417c27031d6a59ff8f3582640365eda16f384657c7c58091baab9e6

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:bb048973d4b4da7e46845eea941b747673a17e296db210964746aa1ac85cfb8c

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:d950faf2acf03faad6c8488a867861fa91b09dbe1c6382ad4d4ea3eb8308b857

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=sha256:05ae44f112ea1bd3b4e5dfc2c87ceac58fe33e4cefac0a971e2b041367cdbf64

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=sha256:9572603b5304f176354df7eb836964120bfbcd9c284e3120f91925f5f232329f

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=sha256:8ea971c378ae9e90abfc616457664736c778302253748c26e9c948dcef5ec092

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

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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=sha256:7d4fac42e595f0248cd83169d182fde1b7245ad09a594e77bded4e7bcbb33d1a

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:43.426385Z digest=sha256:26e55d0dc2a9ee28a6dfe1821646d093fac1d4ccaccb04cebb60b837995f7cc1

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=sha256:45afa542c9578a4604ef2a907410dffa0fda4d38c5e4ac4d676f90874c5c8035

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=sha256:48f8313b8180fde322cb3dbb923b7bac34149e1800d73e8f4a1a084c788262d6

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=sha256:5114f9302b6deb9f59a7d0bd31bd17f13089f680413f800f71199015d31344d0

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
unresolved
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=sha256:038aa946fc7daa9f93eaceb8107bafd77b03c0a7ba589137185419cbd0da5476

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=sha256:6d946f660ef5b2966f945c52626e585eace40498938d239274819f188460dcd3

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:52:43.863165Z digest=sha256:ebe473c6269a656075d92d5732c9d98c006a183ae00f13efd19b1e9b9369acd6

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=sha256:1e85f538f135ca4943b1bb01e79f96e2edab5924e3543327ea9fe01e8731a0e6

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=sha256:9e324538ec00c0129cfaaf435560bb5d9268318e042f24443fac81adce9bdd34

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:52:44.071438Z digest=sha256:9d68c7665ace86460592d13288aa7a12fa375eaecc2b6c30f9dc7160d1d2d2d5

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:52:44.129012Z digest=sha256:5868ecffcdc77b2bc5cf5edc42c7d9c8bb793e26bdc19ec9228606b4f095e986

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:52:44.161132Z digest=sha256:e5337a79b7b0a6f7a6e420db41eda90e644dd66c03f2d539c15e8523ff124e8e

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:52:44.224956Z digest=sha256:c2d076f5032cf2840c76cd35de1b548f0b052f27bad59b1d42864a3c17895bfc

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=sha256:974277456400bbb2af7efcb1c8ef19950f040ba7f34c28717ff283902eaeaaaf

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:52:44.381173Z digest=sha256:074965de86c1b75deb37c3a22b2a213e56b638bfb69fd35b007f338b2c232da6

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

Resolution
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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=sha256:3411180b079064dbe770b02f8ef8a2859fa9d2a6a8313813b8487f5855ce476c

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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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:df356290a197bdeeb1483ad78f09c9b763f3eb4633676961347ad9de1c234683

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T10:52:44.672515Z digest=sha256:da79d3599fc1211907101829d7db2c59d0e440d5891dfa101593db8b6b4fcb45

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=sha256:69577af82d1c02fbbf29dd259ec39b138f871018b8bda74c02b91cff888db45c

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:cef69f4afbd5b9e70b995c8dbd11ada1bdb6f23648de2890a7d788217e730929

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

Resolution
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:fc3c0ce0ca585a61fad4835e1c8362c813099a3dca79761ae52bb17b677aaba9

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=sha256:070c6cf8154503fa4c37f732176eba4223daef54809e5289e8ec982c0478196a

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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unresolved
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:c2a8dfb5df4b81a51031765ab95e2c0922e89e18ddae9e886ff9a2cc368e03f0

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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unresolved
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:b8431e14d0a8180f3814984e11ee1dfe8273d63a3cc799c07de2f0a39786a838

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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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=sha256:89ac15f76a3648227474ee01135bd05a94463b969be884f77d2bb88213c6a7b0

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=sha256:5d853b671a572bd8d47c1e6c6e1fe75699dc9fed3d62dcd5a325751492ca4f76

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

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source=arxiv_source observed=2026-08-06T17:54:18.079107Z digest=sha256:13dd54c93d895b1123fb7c0666ea443289b496d79e755ba6d2b3c2544b4d1358