Pith. sign in

Paper Citation Record · LEDGER

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning

As of 7 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 6 inbound Pith citation observations for arXiv:2505.16315.

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

pith.paper-citation-record.v1
2505.16315 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:06:58.875636Z

measured 43 of 43 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:59:21.349196Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T18:02:27.343921Z

Reference resolution

37 of 37 outbound references displayed

  • verified exact0
  • verified fuzzy2
  • unresolved35
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 40e6d876-0ad2-4beb-b3a2-8df8a1fb2637 · outbound

This paper cites A Survey of Large Language Models.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning A Survey of Large Language Models

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.757616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.757616Z digest=sha256:5a64e2d159d4882704314dd374a078c45ffb29ae975bceffa253985c8aa1ea7a

Observation 631cc139-b023-4c6a-a28f-3a51a4978009 · outbound

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

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.761100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.761100Z digest=sha256:27f967edf28bcac1084fd885dbf85ec2686ed644ff2a5614efd4bd4707ddd90a

Observation 34178338-ac09-4965-a898-58b989749e86 · outbound

This paper cites Kimi k1.5: Scaling Reinforcement Learning with LLMs.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.764354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.764354Z digest=sha256:86b98098ecea6988661c220a202cc1a0e7415936b400c2d660b96d902703aa0b

Observation a1ca278f-b4a3-4800-9fc7-c9e82256239e · outbound

This paper cites OpenAI o1 System Card.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning OpenAI o1 System Card

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.767625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.767625Z digest=sha256:623181b1e70a014cb7f731d42302307df5dd3ba43815e8a7c55bf2a27e9cc687

Observation 2e7eda70-d865-4960-aff9-3c5b91c33ffd · outbound

This paper cites Qwq-32b: Embracing the power of reinforcement learning, March 2025.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Qwq-32b: Embracing the power of reinforcement learning, March 2025

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.770887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.770887Z digest=sha256:6811e7dd8e923622102646bf637dccd5a6eb9b25cdeeecfb2db6e571ee313a9c

Observation 37006777-0af7-474e-86ff-e21f40abc57e · outbound

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

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.774554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.774554Z digest=sha256:187cca8782b65aae211f7aa50092d442b356485c53049a849fe4fc1ff71eec5c

Observation 86671df9-d6f7-4882-8d9b-8655307df6fc · outbound

This paper cites The impact of reasoning step length on large language models.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning The impact of reasoning step length on large language models

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:06:59.383134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:06:58.777975Z digest=sha256:4033471d5eb3f9cdf15e413f9e0668af3b9ec69a9bc8d1e24a244ebe87d3b9cb

Observation d68ddd08-8b94-4d77-9574-c3e037422155 · outbound

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

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Chain-of-thought prompting elicits reasoning in large language models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.780961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.780961Z digest=sha256:91b8244e687c5ef09c6bc74d78f71a75ddfd250e0b428d783d735a27c49e52cf

Observation 7863a5f1-ea24-47b8-98a4-8484427ddce8 · outbound

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

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.783881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.783881Z digest=sha256:30380b6e7d84fab2a00f03fb636085ac0d6b9f442a8dec5be54eca16cf13754b

Observation 559b1c77-b436-4690-a958-aeae34291c61 · outbound

This paper cites Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.787156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.787156Z digest=sha256:b0773de41ab14e28587b786a09dc00783e0a3b421f34cecb4e0cfd6332795104

Observation d6fae705-f5e0-4880-98c2-a047458aa56d · outbound

This paper cites A survey of efficient reasoning for large reasoning models: Language, multimodality, and beyond.CoRR, abs/2503.21614, 2025.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning A survey of efficient reasoning for large reasoning models: Language, multimodality, and beyond.CoRR, abs/2503.21614, 2025

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.790732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.790732Z digest=sha256:442f79edc5cb0921da801639b82bc24fc5b2e3a3edff634ec85102f9de0e8226

Observation 596edc00-34c3-4586-b19f-a24e477eb60b · outbound

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

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.793817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.793817Z digest=sha256:c3ea6bc70dbef295e9d7009459291b21b9969f3855813e09c4a9c096697b2512

Observation 3d44e152-b91d-4e7a-8552-d4efc50cb707 · outbound

This paper cites Tokenskip: Controllable chain-of-thought compression in llms.arXiv preprint arXiv:2502.12067, 2025.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Tokenskip: Controllable chain-of-thought compression in llms.arXiv preprint arXiv:2502.12067, 2025

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.797874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.797874Z digest=sha256:85a69268ad57dfbf9f62c7f0c448e4fb63131e075ab2dcfd962ce6cb52194ac3

Observation b353b1f4-4872-485d-aac9-0b57be157502 · outbound

This paper cites Self-Training Elicits Concise Reasoning in Large Language Models.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Self-Training Elicits Concise Reasoning in Large Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.800947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.800947Z digest=sha256:34f9db1c723a5dc55f0013e34427aaa293274c14410c7bb4cad017a4d5c5daab

Observation 1e3d892d-cbc6-4b61-838f-cca9455213e3 · outbound

This paper cites Demystifying Long Chain-of-Thought Reasoning in LLMs.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Demystifying Long Chain-of-Thought Reasoning in LLMs

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.804399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.804399Z digest=sha256:6fc471cf93aa35a8809b4c9255f80069fdccf893a1824c370bcb2da64b3db07e

Observation eab8a010-3810-459a-8f34-765aef0d4436 · outbound

This paper cites ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement Learning.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement Learning

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.807563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.807563Z digest=sha256:2cba437ec1c4f03b019074f8fbe7ee8d00f2043ed4294330f365bfacd57533b3

Observation 9ce75ed7-72fb-49b6-a397-64450dfdd3f4 · outbound

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

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.810890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.810890Z digest=sha256:ab626246640f99929d909168cab39736b2d228271c1ceb2da0fc9d839c7872a0

Observation e781f5d7-331d-4568-8405-279cc34d151f · outbound

This paper cites Dast: Difficulty-adaptive slow-thinking for large reasoning models.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Dast: Difficulty-adaptive slow-thinking for large reasoning models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.814572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.814572Z digest=sha256:71adcf07ae198ff0fa243bbd5e9bbde50175066b0f3725551ca118744aa5c5f0

Observation e8fb5eb0-a2f1-43ce-b432-574500221f0e · outbound

This paper cites Thinking, fast and slow.Farrar, Straus and Giroux, 2011.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Thinking, fast and slow.Farrar, Straus and Giroux, 2011

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.818080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.818080Z digest=sha256:afe3bf5c5c2f0a215575cb8e0bdc798a41a6690fe3c0bd0bf8ee55dc697830dc

Observation 97a01589-3817-4871-98c8-61efd9896d47 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.821434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.821434Z digest=sha256:85c770423c50a1186f933b045eb331b51ea74186b5988288ecdeaf8aecd1f040

Observation 3d7de5d4-2103-433c-97d1-18a516d19133 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Proximal Policy Optimization Algorithms

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.824688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.824688Z digest=sha256:260fe7dd117d1d0fb9d8190ded9338205654ef1b6c3e4e8cdf260a89b57fcc77

Observation 93029c25-a3a0-4fa0-89d8-bb662725937a · outbound

This paper cites LIMO: Less is More for Reasoning.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning LIMO: Less is More for Reasoning

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.827932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.827932Z digest=sha256:bec4866fc2185366f2b0f70c49e5e7948241e62a5a61f5d2ca57ec50f3d5a545

Observation 19124775-f016-4cf3-a790-a55026db63b2 · outbound

This paper cites Towards thinking-optimal scaling of test-time compute for llm reasoning.arXiv preprint arXiv:2502.18080, 2025.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Towards thinking-optimal scaling of test-time compute for llm reasoning.arXiv preprint arXiv:2502.18080, 2025

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.831772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.831772Z digest=sha256:2b44a95213699aa8b3b3d0caa116d5ba9b417a981fd980fbcc1d329b5ee94c77

Observation 0be56c47-d2ea-4c84-9c2d-d7e46ed6075d · outbound

This paper cites GPT-4 Technical Report.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning GPT-4 Technical Report

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.835438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.835438Z digest=sha256:3be78e913838360f11a73177bf25d7514a3034b2a0ed19d532155768aa70a153

Observation 7c0c6fcb-e9e2-4468-9472-d6f18b9adbbc · outbound

This paper cites Tang, Manan Roongta, Colin Cai, Jeffrey Luo, Li Erran Li, Raluca Ada Popa, and Ion Stoica.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Tang, Manan Roongta, Colin Cai, Jeffrey Luo, Li Erran Li, Raluca Ada Popa, and Ion Stoica

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.838844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.838844Z digest=sha256:e7f645e50ce966cf4b45fb18d0f567b83e8695c9ec13840b4c68137bfd1b6dfa

Observation ae6bea58-246b-4a2f-afdb-9148b5a5af40 · outbound

This paper cites Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.842174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.842174Z digest=sha256:35965ac5eee2408978bf327b253016870ebbf01198bb8f5c432c5c10c3108292

Observation 16e0138a-47f6-4a22-a5af-f5ae87c620b8 · outbound

This paper cites Imitate, Explore, and Self-Improve: A Reproduction Report on Slow-thinking Reasoning Systems.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Imitate, Explore, and Self-Improve: A Reproduction Report on Slow-thinking Reasoning Systems

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.845789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.845789Z digest=sha256:b127de00e759b073861dc7b0e110e150772aa760d73ddcde9125d82755a03399

Observation 92ec3b08-f1f1-473b-ad08-f51d53c6d44d · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Training Verifiers to Solve Math Word Problems

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.848805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.848805Z digest=sha256:cee9f8d6c715ad63d7767531a2b4a266e271ad8f925694c17170d7d271ffd445

Observation 8e392a9d-02ff-4e98-a703-af81e18f3af8 · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Measuring Mathematical Problem Solving With the MATH Dataset

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.851992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.851992Z digest=sha256:3b39d9851939e3c5bf989d8cccda03314b3e77c89e4081f379d82d229090e523

Observation b269056b-7064-4c75-b208-6816f62a1007 · outbound

This paper cites CoT-Valve: Length-Compressible Chain-of-Thought Tuning.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning CoT-Valve: Length-Compressible Chain-of-Thought Tuning

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.854861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.854861Z digest=sha256:76f0660cd5b672664872d96f33806d76ff5fab309ca97a873f10129808253ec2

Observation 044889fb-6f67-40bc-ace4-a159533a2574 · outbound

This paper cites Simpo: Simple preference optimization with a reference-free reward.Advances in Neural Information Processing Systems, 37:124198–124235, 2024.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Simpo: Simple preference optimization with a reference-free reward.Advances in Neural Information Processing Systems, 37:124198–124235, 2024

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.857808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.857808Z digest=sha256:6698c55249a29674ea0d48c9f02b6f4ead96763d82e6691829b9954162ff77ee

Observation c4f6bcfe-4f23-4d51-b594-9c2e2b636817 · outbound

This paper cites verl: V olcano engine reinforcement learning for llms.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning verl: V olcano engine reinforcement learning for llms

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:06:59.353240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T15:06:58.860545Z digest=sha256:8286a827e8d9c83cc81f01628d2c8a957d6acabe121809180aea8d98490fa31a

Observation a1b76cd7-a7ca-4d6f-a460-fff577dd0fa1 · outbound

This paper cites System-1.x: Learning to Balance Fast and Slow Planning with Language Models.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning System-1.x: Learning to Balance Fast and Slow Planning with Language Models

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.863587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.863587Z digest=sha256:0d7c7b85815ec3d233b5f13726b4069499632665d9c765f2f03fad0c025ac0f4

Observation 7e0fbd0d-2620-4af3-b02d-46896bac3c29 · outbound

This paper cites Visual Agents as Fast and Slow Thinkers.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Visual Agents as Fast and Slow Thinkers

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.866572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.866572Z digest=sha256:8d42863986be66e35fd70267116033a5268fc87d3246780819cadddc2674976e

Observation bf34db47-73be-4c31-9063-cbaad67c715d · outbound

This paper cites Think More, Hallucinate Less: Mitigating Hallucinations via Dual Process of Fast and Slow Thinking.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Think More, Hallucinate Less: Mitigating Hallucinations via Dual Process of Fast and Slow Thinking

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.869704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.869704Z digest=sha256:ce6a749e95479719f032e25bc6c5c058e00ddbb65779ac7f473886b00a1b8293

Observation 757f813f-95bb-4880-9028-c6a936323c1c · outbound

This paper cites DynaThink: Fast or Slow? A Dynamic Decision-Making Framework for Large Language Models.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning DynaThink: Fast or Slow? A Dynamic Decision-Making Framework for Large Language Models

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.872574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.872574Z digest=sha256:13f38d1b7e6c9ce5afa71b32f281d83b98d04c6dc1e904580dd1d4ebbccd09f4

Observation 5cb68726-9f4e-46b3-82b2-9906673826fe · outbound

This paper cites Qwen2.5 Technical Report.

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning Qwen2.5 Technical Report

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:58.875636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:58.875636Z digest=sha256:a094b209515b346879c6cedda436c3caa04a72804652bc28a6186f37b498acaa

Pith citing papers

Observation 3c4525fe-af41-4fa9-babb-cba72c3fbd0c · 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 Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-14T01:29:57.520620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-14T01:29:56.480020Z digest=sha256:d66ca17196e856ceb9f1b93692193ca9870c59bdf013d45ed72058259d9b34cc

Observation 7342c6b7-5e9f-47ce-b831-622144ed78ea · inbound

Strategic Reflectivism In Intelligent Systems cites this paper.

Strategic Reflectivism In Intelligent Systems Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T12:59:21.349196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:59:21.349196Z digest=sha256:56e66529ee7ab10d8a4d8abdadc98465d768419100f2c70deb61503e1ca8afec

Observation 43790c91-5fa8-4bce-bc02-1aa8b6fb833a · 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 Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T17:53:43.511503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:53:43.511503Z digest=sha256:4bfa75f0006fb6645f0280d156c2286d94f3135f2d2dff32115fba19bc046cd0

Observation 82e4c9ce-b853-4b1c-a4c7-d729b8a64fd5 · inbound

ConPress: Learning Efficient Reasoning from Multi-Question Contextual Pressure cites this paper.

ConPress: Learning Efficient Reasoning from Multi-Question Contextual Pressure Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-03T05:43:53.034813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:43:53.034813Z digest=sha256:fec063b54fb6443ac70da42f4b99176a8b37926e790b618c43b6cff6cc88091d

Observation 4abc1421-51de-4d05-8a8f-4dcea382e645 · 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 Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning

Reference 246

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T20:06:09.794099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-08T10:19:08.451445Z digest=sha256:be917daae1cc904d78b74f295a367858bfd8a955ee6e27f3a0d2c2bb828bb7c6

Observation 6c760e19-6127-4138-9599-611d73c04bdd · inbound

ThinkSwitch: Context Distillation with LoRA and Weight Interpolation for Specific-Purpose Reasoning Tasks cites this paper.

ThinkSwitch: Context Distillation with LoRA and Weight Interpolation for Specific-Purpose Reasoning Tasks Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning

Reference 50

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T18:02:27.345616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-28T17:52:59.979543Z digest=sha256:8ac4404bf9f87016ecab57084a4619dce2f749ac5a2d498e6b9d35be8dffa109