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Paper Citation Record · LEDGER

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning

As of 19 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 1 inbound Pith citation observation for arXiv:2505.15276.

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

pith.paper-citation-record.v1
2505.15276 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:25:48.530304Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:54:18.134126Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:54:18.275368Z

Reference resolution

32 of 32 outbound references displayed

  • verified exact2
  • verified fuzzy1
  • unresolved29
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2dda9f82-5159-478a-ae2d-f3c3c17c6ce3 · outbound

This paper cites online" 'onlinestring :=.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning online" 'onlinestring :=

Reference 1

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no resolver link, observed 2026-08-07T15:25:46.895611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:46.895611Z digest=sha256:fb748b6d81e27584cbf6ddacf82c0ea31893f559c3e87b261c53416925dadb69

Observation 7158a73c-ebe4-45e1-93b2-be49ce94950e · outbound

This paper cites write newline.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning write newline

Reference 2

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no resolver link, observed 2026-08-07T15:25:46.969543Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:46.969543Z digest=sha256:e3c74fef5184860290c1cbad47605160918e0d657adf42400905fd255834d29c

Observation 48c4bc4c-40b1-44be-b2ad-630f09d1fb9c · outbound

This paper cites L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning

Reference 3

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no resolver link, observed 2026-08-07T15:25:47.031959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:47.031959Z digest=sha256:aacaf86fffb99dd5e20006a8787e337ff15fbb61fe03a005ca84f8c20e77550a

Observation 5b9c94d2-0d15-47b6-8e69-c531f8a9a3e7 · outbound

This paper cites Mathify: Evaluating Large Language Models on Mathematical Problem Solving Tasks.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Mathify: Evaluating Large Language Models on Mathematical Problem Solving Tasks

Reference 4

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verified exact
local_arxiv, observed 2026-08-07T15:25:49.048617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T15:25:47.084141Z digest=sha256:5b4f3395db37e8aff055f67bc17b6e878c642741beb586da70992f91b64c8e2e

Observation 20e7d7f3-19c8-4d16-9ee3-bb473ff2a0bf · outbound

This paper cites Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models

Reference 5

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no resolver link, observed 2026-08-07T15:25:47.124956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:47.124956Z digest=sha256:92f13d44f6b6cd932ad7ff4c76bd7281163dc4bc68aa3d3dc3b3479dad66536e

Observation e382bb8b-1608-4342-8047-fb596c48d096 · outbound

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

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs

Reference 6

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no resolver link, observed 2026-08-07T15:25:47.164256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:47.164256Z digest=sha256:98bd52a822872353db4c24b78829b50b942f4c813a5365149ffca1ae0b0397f4

Observation d2310bac-7a86-408e-8d27-06de66e977c8 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Training Verifiers to Solve Math Word Problems

Reference 7

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no resolver link, observed 2026-08-07T15:25:47.232594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:47.232594Z digest=sha256:2bb22cec5dbc01494ba44e9df35e3d409c1fad83c83b4aac11780b0057330693

Observation 15a6e827-8ae6-4fef-8909-da8cdff998a2 · outbound

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

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 8

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no resolver link, observed 2026-08-07T15:25:47.288878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:47.288878Z digest=sha256:0b86cac822edde7d94f840af8286e7d5241de795ea80fcbac3e98b45c5ddacbc

Observation aca8fdb3-7bbe-4418-8bd1-be865449d35b · outbound

This paper cites DeepSeek-V3 Technical Report.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning DeepSeek-V3 Technical Report

Reference 9

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no resolver link, observed 2026-08-07T15:25:47.342960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:47.342960Z digest=sha256:558e74b6594188f782f2017ac7842fa80a0fb71824a7eeef1a2cf91c8c1c640e

Observation b712f6aa-865f-473d-9a73-b63fa25cb259 · outbound

This paper cites an unresolved cited work.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Unresolved cited work

Reference 10

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raw_fallback, observed 2026-08-07T15:25:49.712232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T15:25:47.387800Z digest=sha256:be2775716b246ea88f1b3b80aa4202a824487ba0dc2bd315c552f79fb6e44299

Observation 50be68a5-40f7-4b38-9608-f33181707c9f · outbound

This paper cites Token-Budget-Aware LLM Reasoning.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Token-Budget-Aware LLM Reasoning

Reference 11

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no resolver link, observed 2026-08-07T15:25:47.430493Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:47.430493Z digest=sha256:714bdfbcc721d3a63376a5337b659d4b507053ef538529bb86b49dcc3de73245

Observation 1129153e-f04f-4541-b2a7-011376510d2a · outbound

This paper cites an unresolved cited work.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Unresolved cited work

Reference 12

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unresolved
raw_fallback, observed 2026-08-07T15:25:49.622337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T15:25:47.470838Z digest=sha256:cbeb5f730b6a8ca4cc1bfa49c6b398a2f6f5d7873704b65e1f060404697c177a

Observation d9144f32-3f6a-4124-be0e-a342cd2fc897 · outbound

This paper cites u ttler, Mike Lewis, Wen - tau Yih, Tim Rockt \.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning u ttler, Mike Lewis, Wen - tau Yih, Tim Rockt \

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-07T15:25:49.536008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T15:25:47.538867Z digest=sha256:be11cebd0450283b03d5296f7973571c08c0b52d09212d5720d550944fcacd9f

Observation 0f55d79f-5fa8-49ea-ac05-5c2d547af32e · outbound

This paper cites an unresolved cited work.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Unresolved cited work

Reference 14

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unresolved
no resolver link, observed 2026-08-07T15:25:47.589088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:47.589088Z digest=sha256:b0c93ac547b3a69d25824f01c5267a45a8c2e863bda5a1025cd8e398f0f0b258

Observation 2e861286-df0e-46ba-81ff-33c224f1fb8b · outbound

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

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Thought Manipulation: External Thought Can Be Efficient for Large Reasoning Models

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:47.648989Z digest=sha256:9dd069b75b9e84e73d05c0db8c1c3902740917f2f2c71b93d412465b21e59470

Observation 0f19dfa3-fc17-4a23-a171-8e08ee6f2f17 · outbound

This paper cites an unresolved cited work.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Unresolved cited work

Reference 16

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verified exact
doi, observed 2026-08-07T15:25:48.887165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T15:25:47.700787Z digest=sha256:d3ccf1e35665c9e5ebae8ffb4727364dfc8a640224a8d3fe9655fc59118b6c34

Observation ed311d06-cbb6-4948-85d6-d3ed102d0f6a · outbound

This paper cites Reasoning Models Can Be Effective Without Thinking.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Reasoning Models Can Be Effective Without Thinking

Reference 17

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unresolved
no resolver link, observed 2026-08-07T15:25:47.751542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:47.751542Z digest=sha256:5c1dfd292d940dfab6e57c38ed9d55f2c51f025a707a4d3c017e52f98a2bad58

Observation 3bb919ec-520d-4399-9a11-2bcc38e7ad96 · outbound

This paper cites an unresolved cited work.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Unresolved cited work

Reference 18

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raw_fallback, observed 2026-08-07T15:25:49.433158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T15:25:47.798910Z digest=sha256:967fb41835e9ecd024e3b406cf1b4d86b2306dd4927a516b30aef51d019394c5

Observation 01a15e2f-0756-49a4-82f8-488e8436cf95 · outbound

This paper cites s1: Simple test-time scaling.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning s1: Simple test-time scaling

Reference 19

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no resolver link, observed 2026-08-07T15:25:47.857077Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:47.857077Z digest=sha256:89d7f8391ef1aa298c3b8245fc888e80eaf1333557fe9830fa73924e91b46358

Observation 48de6ff9-a166-4975-9094-d89072981ec9 · outbound

This paper cites GPT-4 Technical Report.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning GPT-4 Technical Report

Reference 20

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no resolver link, observed 2026-08-07T15:25:47.902365Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:47.902365Z digest=sha256:bb56347a0b68907db046785e6e562e086f9992e1b5195fb5cc78883ed73a5080

Observation 217a0895-3f8b-4188-b848-6c89f635a91b · outbound

This paper cites an unresolved cited work.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Unresolved cited work

Reference 21

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unresolved
raw_fallback, observed 2026-08-07T15:25:49.344098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T15:25:47.974474Z digest=sha256:da3bfb6131883c49aea84b1a87d3b612a03452ca8897b2881026175a25168c1d

Observation 9862e8ad-de5e-4de1-a60f-572ecbcd0629 · outbound

This paper cites The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs: An Exhaustive Review of Technologies, Research, Best Practices, Applied Research Challenges and Opportunities.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs: An Exhaustive Review of Technologies, Research, Best Practices, Applied Research Challenges and Opportunities

Reference 22

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no resolver link, observed 2026-08-07T15:25:48.017209Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:48.017209Z digest=sha256:53263c405da223a86bb4d9bca50a031706114ade75e987d43d0b4d960c242fc6

Observation 67d9088e-a32b-4723-8867-4a9ef489ad46 · outbound

This paper cites Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning

Reference 23

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no resolver link, observed 2026-08-07T15:25:48.065006Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:48.065006Z digest=sha256:a4616bda7dce019cffdee9c462a7eba58cf4eb8cf7631c8d3114d56e2c4f3d2a

Observation 7561e2aa-27b4-44ae-97ee-da057d68c799 · outbound

This paper cites an unresolved cited work.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Unresolved cited work

Reference 24

Resolution
unresolved
raw_fallback, observed 2026-08-07T15:25:49.268275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T15:25:48.121522Z digest=sha256:726c288a0ffbb8cf2810c618da346bd36c457120ac708cd5513f4d4964816619

Observation 7efa5a83-f7f9-4d8a-bad1-05507801e2f3 · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 25

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no resolver link, observed 2026-08-07T15:25:48.190884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:48.190884Z digest=sha256:b309a25a20ba749a3c2c14aee7965e43191cdba4b466814ae79210c3eccc3872

Observation 4229cc8a-6a5b-46c4-924d-13553699e247 · outbound

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

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models

Reference 26

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unresolved
no resolver link, observed 2026-08-07T15:25:48.238572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:48.238572Z digest=sha256:eafe11179c11304a0b241a4bad8ec48a917347b8f138bcc739e453ba99b8737d

Observation 6bd0f2a5-b555-4c70-89d9-249b0936b9f7 · outbound

This paper cites Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models

Reference 27

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unresolved
no resolver link, observed 2026-08-07T15:25:48.278659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:48.278659Z digest=sha256:6888f34d7e9848add907f2075a023847da0db6ecd0a01ef7a02eaf8413b04061

Observation 7c1fc73b-cab9-4220-824f-2ca048e0b9f2 · outbound

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

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Chain of Draft: Thinking Faster by Writing Less

Reference 28

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unresolved
no resolver link, observed 2026-08-07T15:25:48.328140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:48.328140Z digest=sha256:9dddd7d60b4012858ba75533d82bb78cffbfc6f1aa6b97da136120c881500b7f

Observation 8d9baae8-3f74-49b6-9e3b-e98bbb963281 · outbound

This paper cites Qwen2.5 Technical Report.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Qwen2.5 Technical Report

Reference 29

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unresolved
no resolver link, observed 2026-08-07T15:25:48.388434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:48.388434Z digest=sha256:19863a71f7f341b0e399c027de1833390a633b6e6983fb0f72a49284cb08d6a3

Observation 692f2d51-8c57-4511-a186-f380d0fa49ab · outbound

This paper cites an unresolved cited work.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Unresolved cited work

Reference 30

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unresolved
no resolver link, observed 2026-08-07T15:25:48.424721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:48.424721Z digest=sha256:321ec746955584ff71899bf2770cca913b950154b3f33d5bff71b3b123362286

Observation dcd1c1ed-c3e5-479d-8543-210379586bcc · outbound

This paper cites A Survey of Large Language Models.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning A Survey of Large Language Models

Reference 31

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unresolved
no resolver link, observed 2026-08-07T15:25:48.470149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:48.470149Z digest=sha256:336f97bdae0380e1d08dd8dd26642df7dbfee59269e73633274fd6ad6a576220

Observation be92d59c-6ca9-45bc-adec-d135ca8ce10f · outbound

This paper cites Mitigating Lost-in-Retrieval Problems in Retrieval Augmented Multi-Hop Question Answering.

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning Mitigating Lost-in-Retrieval Problems in Retrieval Augmented Multi-Hop Question Answering

Reference 32

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unresolved
no resolver link, observed 2026-08-07T15:25:48.530304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:25:48.530304Z digest=sha256:46fdeabaae81b6fb78aae71f33842d7f654e0c1abf09c16516b3548a73f75491

Pith citing papers

Observation 94bc20c2-237f-467c-85ec-0ecb142c8c7d · 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 When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning

Reference 252

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:54:18.282899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-06T17:54:18.134126Z digest=sha256:66f933eea882fb369a43eebd8a64729a33a75bf150c88cc529c87b561d76c21d