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Paper Citation Record · LEDGER

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training

As of 20 August 2026, this Paper Citation Record lists 100 of 104 outbound references and 2 inbound Pith citation observations for arXiv:2505.14681.

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

pith.paper-citation-record.v1
2505.14681 v2

Coverage vector

measured 100 of 104 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:36:06.449701Z

measured 102 of 102 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:07:40.131808Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T07:41:00.572991Z

Reference resolution

100 of 104 outbound references displayed

  • verified exact1
  • verified fuzzy3
  • unresolved96
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dde255fb-69d9-47bf-93b2-26ae663bc741 · outbound

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

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 1

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source=arxiv_source observed=2026-08-07T15:36:06.097425Z digest=sha256:f810a7dd6c85d3a148b37fde7f6bed4bc5b6259b4869021d7cfb8680a72083c2

Observation 3b1004d0-8e86-4ba0-acc9-a77fabcfbf68 · outbound

This paper cites Qwen3: Think deeper, act faster.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Qwen3: Think deeper, act faster

Reference 2

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source=arxiv_source observed=2026-08-07T15:36:06.101934Z digest=sha256:10af5710b3977a8bd07f2cd77c2f68d800a3871d59bee4d4816e64558007e29e

Observation 7cb870a0-b175-494b-89ab-175ec8b24a55 · outbound

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

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs

Reference 3

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source=arxiv_source observed=2026-08-07T15:36:06.106030Z digest=sha256:ceab7a2db3f1f16f711f241c82e1c1737b1e2dec1d17ddaa0dea3d32b1af44e7

Observation c0db09e6-e810-44d4-abf1-02bfcfc35d30 · outbound

This paper cites Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs

Reference 4

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source=arxiv_source observed=2026-08-07T15:36:06.109851Z digest=sha256:a550876b8aae21ec2fe4b3dbc84a2adaa27267b5fd0ca4fa30c28cd1674c541d

Observation 4783dcac-fb81-4275-ae38-5fd299f47c15 · outbound

This paper cites OpenAI o1 System Card.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training OpenAI o1 System Card

Reference 5

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source=arxiv_source observed=2026-08-07T15:36:06.113465Z digest=sha256:14db2d1759e25bda97eef5ce3af6d5d6719e7bdc475b2995c67bddc4ee1c3ca6

Observation 4e3c4d21-5be9-48e6-b420-5b18ebe0fa3d · outbound

This paper cites A Survey of Test-Time Compute: From Intuitive Inference to Deliberate Reasoning.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training A Survey of Test-Time Compute: From Intuitive Inference to Deliberate Reasoning

Reference 6

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source=arxiv_source observed=2026-08-07T15:36:06.117726Z digest=sha256:8a72661da4d433ce32280c9c279f32e90b3e38c75a27226988953c16a6be86c1

Observation 7fe73304-4756-4f24-9074-56cf2419473f · outbound

This paper cites A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 7

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source=arxiv_source observed=2026-08-07T15:36:06.123183Z digest=sha256:fff485fdcc72501ec10263fa32e2e94eec2a35879b81ab29cbc5d22548a95c57

Observation 57d758f3-1b97-4d4c-9d63-46d981c56be9 · outbound

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

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models

Reference 8

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Observation 81a47dd3-d873-4495-8988-dc53c18df9fa · outbound

This paper cites Efficient reasoning models: A survey.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Efficient reasoning models: A survey

Reference 9

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Observation 06417ac6-4910-4b6a-9e4d-268a7dda7ebb · outbound

This paper cites A Survey of Slow Thinking-based Reasoning LLMs using Reinforced Learning and Inference-time Scaling Law.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training A Survey of Slow Thinking-based Reasoning LLMs using Reinforced Learning and Inference-time Scaling Law

Reference 10

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Observation ae20b146-0fc1-4cc3-af29-4eb8d57cdb3f · outbound

This paper cites A survey of efficient reasoning for large reasoning models: Language, multimodality, and beyond.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training A survey of efficient reasoning for large reasoning models: Language, multimodality, and beyond

Reference 11

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source=arxiv_source observed=2026-08-07T15:36:06.137934Z digest=sha256:dd93aee71e6a2d548c972e4477411f97ad1f73b10e8bfc7d38293cdb58c5ae95

Observation f65cceea-64dd-4e52-a487-2a64bd7ad22d · outbound

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

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models

Reference 12

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source=arxiv_source observed=2026-08-07T15:36:06.140959Z digest=sha256:f4cd091b6a9671f2dab3b7db4911e00acd8629f5d2daf6dc361705e480c137aa

Observation d505850f-8613-428d-92aa-6b3fe65699c6 · outbound

This paper cites Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models

Reference 13

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source=arxiv_source observed=2026-08-07T15:36:06.144176Z digest=sha256:59c0f51ff363923b034d11a3b9fde092c4b0e0a410e02b4e93ecdcafae134f9c

Observation b60d7ca0-91c5-4675-9c4f-cf8428f4c72a · outbound

This paper cites Effectively Controlling Reasoning Models through Thinking Intervention.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Effectively Controlling Reasoning Models through Thinking Intervention

Reference 14

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source=arxiv_source observed=2026-08-07T15:36:06.148359Z digest=sha256:1b173d96206f9bf7834178190f227c2be7f2cdc7a50fbe728ec8a1a4092e97e8

Observation 8a37d5ae-d437-49e7-b5da-fe587ff80238 · outbound

This paper cites Retro-Search: Exploring Untaken Paths for Deeper and Efficient Reasoning.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Retro-Search: Exploring Untaken Paths for Deeper and Efficient Reasoning

Reference 15

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Observation b8c25046-715d-449f-a15b-5b191ea71827 · outbound

This paper cites DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Reference 16

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Observation 0dc9d088-f9ff-4413-bb47-904575b278b9 · outbound

This paper cites DeepSeek-V3 Technical Report.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training DeepSeek-V3 Technical Report

Reference 17

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Observation c206e5a1-23d3-4b36-8897-683c6425109e · outbound

This paper cites Openmoe: An early effort on open mixture-of-experts language models.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Openmoe: An early effort on open mixture-of-experts language models

Reference 18

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Observation c990ef0d-fcc4-4993-9f05-81e58639c231 · outbound

This paper cites Working memory revived in older adults by synchronizing rhythmic brain circuits.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Working memory revived in older adults by synchronizing rhythmic brain circuits

Reference 19

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Observation 6b7a775e-ae93-4b40-8181-20ffd9316f43 · outbound

This paper cites Neurocognitive, physiological, and biophysical effects of transcranial alternating current stimulation.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Neurocognitive, physiological, and biophysical effects of transcranial alternating current stimulation

Reference 20

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Observation d17cbb26-00f2-4e3f-a922-56a8d91ed203 · outbound

This paper cites Non-invasively targeting, probing and modulating a deep brain circuit for depression alleviation.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Non-invasively targeting, probing and modulating a deep brain circuit for depression alleviation

Reference 21

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source=arxiv_source observed=2026-08-07T15:36:06.172423Z digest=sha256:ff391b011f0adb34b0a841253b9f77293906fe6c7cabca18348b4a3c5d151174

Observation b1184e70-71e2-4c89-b1b1-522fdb5efd50 · outbound

This paper cites High-frequency neuromodulation improves obsessive--compulsive behavior.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training High-frequency neuromodulation improves obsessive--compulsive behavior

Reference 22

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Observation 545a8398-fcec-43c7-b945-6dee6d11de97 · outbound

This paper cites Normalized (pointwise) mutual information in collocation extraction.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Normalized (pointwise) mutual information in collocation extraction

Reference 23

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source=arxiv_source observed=2026-08-07T15:36:06.179680Z digest=sha256:8d075b24546e6fe7a6597bea5ccf846e64ab181be9b7ad2a4ec728fac664e0c4

Observation 1a989082-7d23-4866-bb14-cfc11d4a0626 · outbound

This paper cites Probing Semantic Routing in Large Mixture-of-Expert Models.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Probing Semantic Routing in Large Mixture-of-Expert Models

Reference 24

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source=arxiv_source observed=2026-08-07T15:36:06.182908Z digest=sha256:e2f55e07daf6f9c69c7d46488f25ade6ea2d69e1518b7bd93bddb05c18cc240d

Observation f5dcdb0a-850b-4959-afec-a43d3f4b3289 · outbound

This paper cites Aime problems and solutions.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Aime problems and solutions

Reference 25

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Observation 4bdc1b01-9dba-49fc-89cb-5c654b19086f · outbound

This paper cites an unresolved cited work.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Unresolved cited work

Reference 26

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Observation c7d0f578-3ee1-4e05-a0dc-10afd508885d · outbound

This paper cites From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline

Reference 27

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source=arxiv_source observed=2026-08-07T15:36:06.195570Z digest=sha256:edbe53edc41be48410c7b4d57ca1695adfeb6c4fe72829ae37905446c74f6057

Observation a8d377b7-92dc-41a7-bb44-ead145118e50 · outbound

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

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Generative AI Act II: Test Time Scaling Drives Cognition Engineering

Reference 28

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source=arxiv_source observed=2026-08-07T15:36:06.199466Z digest=sha256:3d6d76ea1357ad94f80487f7035e8e678023b767f639affccc47ef07399028b5

Observation e50066b5-1817-45f6-a1cd-4897491e5557 · outbound

This paper cites Qwq: Reflect deeply on the boundaries of the unknown.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Qwq: Reflect deeply on the boundaries of the unknown

Reference 29

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source=arxiv_source observed=2026-08-07T15:36:06.203634Z digest=sha256:4d11e55d9cf0d01ac2356f31d2966f81bc9f1862ac5d39461db4656b5c8e6b82

Observation 874b3349-7f6b-497e-b1ae-1d942749facb · outbound

This paper cites Claude 3.7 sonnet.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Claude 3.7 sonnet

Reference 30

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source=arxiv_source observed=2026-08-07T15:36:06.206752Z digest=sha256:9d497e833d4d75b73c3ff9d95ab7f362016fe991f4132f2f94541a648cccad6e

Observation 8843a690-5b26-41b2-ad6e-60025642029c · outbound

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

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 31

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Observation cea28f27-83b8-4804-a994-4846600618d7 · outbound

This paper cites an unresolved cited work.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Unresolved cited work

Reference 32

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source=arxiv_source observed=2026-08-07T15:36:06.213155Z digest=sha256:e79b59070be2a0ee76a64dbbfeff4888785a39d71cd6cf8011a57cf9f68f085f

Observation 1f6994b1-f328-45bc-8184-b65ecc33ec7a · outbound

This paper cites The llama 4 herd: The beginning of a new era of natively multimodal ai innovation.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training The llama 4 herd: The beginning of a new era of natively multimodal ai innovation

Reference 33

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Observation 1d150de9-74ed-4206-9810-1cea3a9a15db · outbound

This paper cites OLMoE: Open Mixture-of-Experts Language Models.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training OLMoE: Open Mixture-of-Experts Language Models

Reference 34

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source=arxiv_source observed=2026-08-07T15:36:06.219070Z digest=sha256:f3f923937cb659d026328f20ffb6d96e44c39d101e37eb44212fc1dbe297fc50

Observation 9d1d7fcb-05d2-45dd-96bc-5ae5793625d6 · outbound

This paper cites Le, Geoffrey E.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Le, Geoffrey E

Reference 35

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source=arxiv_source observed=2026-08-07T15:36:06.222795Z digest=sha256:49d1348f62e780ace4e9084b8c553900890780fef375850fa958e4d03556e158

Observation 11723429-ce56-481e-bf43-948f023e8b90 · outbound

This paper cites Mixture of Tunable Experts -- Behavior Modification of DeepSeek-R1 at Inference Time.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Mixture of Tunable Experts -- Behavior Modification of DeepSeek-R1 at Inference Time

Reference 36

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source=arxiv_source observed=2026-08-07T15:36:06.226587Z digest=sha256:a7d2813fb4196a20fbda59a94eab55cd2dcb1d1a46499fe4900485ef64084f3c

Observation a2c38890-4b3d-4cbf-8d23-c8c4b35b65ec · outbound

This paper cites Under the hood of a reasoning model.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Under the hood of a reasoning model

Reference 37

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no resolver link, observed 2026-08-07T15:36:06.230426Z

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source=arxiv_source observed=2026-08-07T15:36:06.230426Z digest=sha256:0b89437754886a957ad72396ad1d184015921eac72691502814bf09e41c3fb8a

Observation fdff6091-894d-47a2-9361-38318dccc481 · outbound

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

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models

Reference 38

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no resolver link, observed 2026-08-07T15:36:06.233904Z

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source=arxiv_source observed=2026-08-07T15:36:06.233904Z digest=sha256:67262bbf994a088f53365f6b06125064ca76304c968d9dd27203b786a91a4300

Observation 3599f3c2-c32f-4c1b-9b91-08c8c01615e6 · outbound

This paper cites The Danger of Overthinking: Examining the Reasoning-Action Dilemma in Agentic Tasks.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training The Danger of Overthinking: Examining the Reasoning-Action Dilemma in Agentic Tasks

Reference 39

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source=arxiv_source observed=2026-08-07T15:36:06.237359Z digest=sha256:33a784100b0aec342da25f939291b454a0580e5a2f1ec76673ac4805b349ecff

Observation ca3d24b8-33bf-48f6-950d-d073526d2b13 · outbound

This paper cites Trading Inference-Time Compute for Adversarial Robustness.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Trading Inference-Time Compute for Adversarial Robustness

Reference 40

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source=arxiv_source observed=2026-08-07T15:36:06.241064Z digest=sha256:403750d5d165fe9cc79f540f86036a93a8ac9ac958b121d4798a88bb84fcfdde

Observation fb42e7d4-88d1-4b98-a70c-9a1a12e0f147 · outbound

This paper cites The relationship between reasoning and performance in large language models--o3 (mini) thinks harder, not longer.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training The relationship between reasoning and performance in large language models--o3 (mini) thinks harder, not longer

Reference 41

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source=arxiv_source observed=2026-08-07T15:36:06.244296Z digest=sha256:8c2263c8d997bafa22cce7919ce8d3976316e18f8bfe103cf2adf4efe3c62e5a

Observation 8b2b8ab6-f233-4d67-893c-1e784f71941c · outbound

This paper cites Learning to Stop Overthinking at Test Time.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Learning to Stop Overthinking at Test Time

Reference 42

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no resolver link, observed 2026-08-07T15:36:06.248333Z

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source=arxiv_source observed=2026-08-07T15:36:06.248333Z digest=sha256:1b48f573053b178f9c9ed117da7228bbbaa56baa0bdc62fe787ae5b3375ba525

Observation 0eef2f8d-8868-4796-b00b-0a76d99d611e · outbound

This paper cites Dynamic Parallel Tree Search for Efficient LLM Reasoning.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Dynamic Parallel Tree Search for Efficient LLM Reasoning

Reference 43

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no resolver link, observed 2026-08-07T15:36:06.251549Z

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source=arxiv_source observed=2026-08-07T15:36:06.251549Z digest=sha256:39a29cf580a8130f77fda7ac234acf64843e929d6389900e3b3f3ed9aea76826

Observation fa462b08-872f-457b-96c4-99548657c1f1 · outbound

This paper cites Can Atomic Step Decomposition Enhance the Self-structured Reasoning of Multimodal Large Models?.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Can Atomic Step Decomposition Enhance the Self-structured Reasoning of Multimodal Large Models?

Reference 44

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source=arxiv_source observed=2026-08-07T15:36:06.256005Z digest=sha256:0ca014adc7fe2a261b12bc254abbc4e4fdbb3776976a33f2e5a29bdd25b160c4

Observation a40f1f38-edaf-4ab6-b4b3-435222c6dbad · outbound

This paper cites Reasoning Models Can Be Effective Without Thinking.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Reasoning Models Can Be Effective Without Thinking

Reference 45

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source=arxiv_source observed=2026-08-07T15:36:06.259987Z digest=sha256:edf2ef9972759bfa82eb2fbadd6c6a362438907c1b94dfd1dbd1d8e4e3d55a69

Observation d26b707b-19cd-40f1-af7d-85666a99ddf2 · outbound

This paper cites s1: Simple test-time scaling.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training s1: Simple test-time scaling

Reference 46

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source=arxiv_source observed=2026-08-07T15:36:06.263321Z digest=sha256:f5a5aee7d46d1e28813eaf3a1df1e3ba21a9c78090324a9ab7c88fbbcf5f5bf5

Observation e0de894f-502b-4ab2-9710-ef5f52d0ae58 · outbound

This paper cites Token-Budget-Aware LLM Reasoning.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Token-Budget-Aware LLM Reasoning

Reference 47

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source=arxiv_source observed=2026-08-07T15:36:06.266706Z digest=sha256:582c57b8b47fd68442817546e3c9d4cd454b8900f909a67dba88e4daf6c7dc3e

Observation ddf7d854-3cc9-4a7e-a8b5-cc892e465656 · outbound

This paper cites Aytes, Jinheon Baek, and Sung Ju Hwang.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Aytes, Jinheon Baek, and Sung Ju Hwang

Reference 48

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source=arxiv_source observed=2026-08-07T15:36:06.270087Z digest=sha256:e3048e2572e081f73ef20505f9e0dd184e1b9238649aeec1561205c8a3b22042

Observation 920b4382-3696-4fc2-a1c0-e3937411a2bd · outbound

This paper cites Lightthinker: Thinking step-by-step compression.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Lightthinker: Thinking step-by-step compression

Reference 49

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source=arxiv_source observed=2026-08-07T15:36:06.273270Z digest=sha256:0d93c19647196bf36e58a32cce95ffded534462bf9c469f34c70d252e3eb7013

Observation 59372352-24a5-439e-a24c-4eb217982bc5 · outbound

This paper cites Seal: Steerable reasoning calibration of large language models for free.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Seal: Steerable reasoning calibration of large language models for free

Reference 50

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source=arxiv_source observed=2026-08-07T15:36:06.276350Z digest=sha256:4c37d67e1496dd5e5c3ecbbed196fb48c817e841632dd962127413c872d0a367

Observation 211e0d5a-ec77-4f57-9028-ae44158348f6 · outbound

This paper cites Steering the CensorShip: Uncovering Representation Vectors for LLM "Thought" Control.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Steering the CensorShip: Uncovering Representation Vectors for LLM "Thought" Control

Reference 51

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no resolver link, observed 2026-08-07T15:36:06.279507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:36:06.279507Z digest=sha256:cacabec7e89ca800a08c2102e0902d60300c8519174703abb244a114d99d43fe

Observation 5de77e3d-851e-4323-808f-0ca3b53aa012 · outbound

This paper cites Thinkedit: Interpretable weight editing to mitigate overly short thinking in reasoning models.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Thinkedit: Interpretable weight editing to mitigate overly short thinking in reasoning models

Reference 52

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no resolver link, observed 2026-08-07T15:36:06.283460Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T15:36:06.283460Z digest=sha256:43729d5eeb66e0c0e7da44d691400c235368c4ef7aa02dbcf1308ac09ae21898

Observation 06a73e45-0374-4964-984f-18b422e6f7fd · outbound

This paper cites LIMO: Less is More for Reasoning.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training LIMO: Less is More for Reasoning

Reference 53

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T15:36:06.287504Z digest=sha256:a3465fc3fb0387430c2ae54cdb72bf4cc328d9d423d58ee723e02a90afd0e5b5

Observation 0bce3938-2fec-42c9-8b12-b0a81ee85ddd · outbound

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

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning

Reference 54

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T15:36:06.290884Z digest=sha256:517f2d2d800f755bbf47c5e81c51df592fca97a51784b30b6181e188314255bf

Observation 5ca71676-a3cc-45af-b056-808f460aa723 · outbound

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

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Training Large Language Models to Reason in a Continuous Latent Space

Reference 55

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no resolver link, observed 2026-08-07T15:36:06.294059Z

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source=arxiv_source observed=2026-08-07T15:36:06.294059Z digest=sha256:3f9371dcaebe05c2a13d9982f8728a694f1770eb9a21450c4a71812cd5bb5988

Observation 9bab0c8e-bce7-46b5-aec0-628e49a04412 · outbound

This paper cites C3PO: Critical-Layer, Core-Expert, Collaborative Pathway Optimization for Test-Time Expert Re-Mixing.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training C3PO: Critical-Layer, Core-Expert, Collaborative Pathway Optimization for Test-Time Expert Re-Mixing

Reference 56

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no resolver link, observed 2026-08-07T15:36:06.297512Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T15:36:06.297512Z digest=sha256:3913e258fb79c5eea81797412dc6df98544f9853f03995049396a75a176432f8

Observation 413e6c4f-a0ef-4bf0-8058-7d9f858e2d28 · outbound

This paper cites Unveiling Hidden Collaboration within Mixture-of-Experts in Large Language Models.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Unveiling Hidden Collaboration within Mixture-of-Experts in Large Language Models

Reference 57

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local_arxiv, observed 2026-08-07T15:36:06.897941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:36:06.300609Z digest=sha256:243931f17c84de5667d024d5cba29393288793e29f8cc42ef7fe9a9a6e1b3289

Observation 74c62790-e0fe-4152-bc5b-56ac50717ced · outbound

This paper cites @esa (Ref.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training @esa (Ref

Reference 58

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source=arxiv_source observed=2026-08-07T15:36:06.304924Z digest=sha256:ad2731f1433a32c20f58d29549da1d556c2656993002495ed3345b704ee95e5f

Observation 4cbca74a-98a1-415f-85ad-e34903769a76 · outbound

This paper cites an unresolved cited work.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Unresolved cited work

Reference 59

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source=arxiv_source observed=2026-08-07T15:36:06.308588Z digest=sha256:9dc4df8fe6a0bedb8b2573059d6c09a46be39103ca647317d280a7acd5d6189f

Observation 85696020-767c-4186-ba30-4a7059a76822 · outbound

This paper cites an unresolved cited work.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Unresolved cited work

Reference 60

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source=arxiv_source observed=2026-08-07T15:36:06.312141Z digest=sha256:eb8de2f795aaada64c86e2580070b77e44bdc6de1c88a0bf16dd5737bd76fe09

Observation 5668d442-49b1-4bcc-94a6-b89a4d34bfd5 · outbound

This paper cites an unresolved cited work.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Unresolved cited work

Reference 61

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T15:36:06.315624Z digest=sha256:6c4eeeea44ea7da3a2ec4a702cd642148998ccebcb6d0c312d94dce90e3e6ed2

Observation 21abcae5-f18a-4f40-b107-0720c7b7cd6f · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 62

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T15:36:06.318473Z digest=sha256:e96d6f68ab47102c48130bf0e8f232ca8bbe203ec8fb83064044865ae71a8e5e

Observation 20a64d52-2935-47af-b9c1-a553aa111a4b · outbound

This paper cites GPT-4 Technical Report.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training GPT-4 Technical Report

Reference 63

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no resolver link, observed 2026-08-07T15:36:06.321890Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T15:36:06.321890Z digest=sha256:d3b6c5116ac1f2345890039ea5f750856279c12bae28ebd400586ec2614c643e

Observation 09662989-9801-4a1f-a2ad-27e8eee8589a · outbound

This paper cites COIG-CQIA: Quality is All You Need for Chinese Instruction Fine-tuning.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training COIG-CQIA: Quality is All You Need for Chinese Instruction Fine-tuning

Reference 64

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T15:36:06.325426Z digest=sha256:a094b10f787d11a4b69dae4e53f51dcb5b0e60e0935d6000aca1770ca8adf4ba

Observation 52a9be16-ce12-44b2-adee-e2b3b92fdbcd · outbound

This paper cites Comprehensive Exploration of Synthetic Data Generation: A Survey.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Comprehensive Exploration of Synthetic Data Generation: A Survey

Reference 65

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source=arxiv_source observed=2026-08-07T15:36:06.328740Z digest=sha256:f71d94a9848415c8c24c3e913c40875d3d1f5accc5cf1841e68880c904766d6a

Observation c5aa4bde-b879-4805-9a29-7d54defcacc7 · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 66

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source=arxiv_source observed=2026-08-07T15:36:06.332583Z digest=sha256:31537ec8e59023fca6d40d5f19f7854014869897b2e33a9a6da4e019aa4812c4

Observation f90a61bc-80c7-44b3-b79d-3bf89ca6a168 · outbound

This paper cites On the resemblance and containment of documents.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training On the resemblance and containment of documents

Reference 67

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source=arxiv_source observed=2026-08-07T15:36:06.335828Z digest=sha256:6f8e375d1edafd90334210d016e0be16c073c8c84cf8c347c0c32a85bd67c293

Observation 0d88b97c-7e2b-4861-9c60-b23408cca9f8 · outbound

This paper cites Large Language Models as Tool Makers.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Large Language Models as Tool Makers

Reference 68

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T15:36:06.338637Z digest=sha256:275d62b6a15e74d6b0e6e81a44631d2a3f8d3a127b3d5384284e0510b607ee9e

Observation afa15b21-dbdf-4136-ba27-ff584da8e596 · outbound

This paper cites On the Possibilities of AI-Generated Text Detection.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training On the Possibilities of AI-Generated Text Detection

Reference 69

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no resolver link, observed 2026-08-07T15:36:06.342022Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T15:36:06.342022Z digest=sha256:7412720639562ce3f32712278dee92addaea0ad98ac3a323cbc5a154c95716d0

Observation 21b7229e-1fbf-4a27-b830-66a15c5cadb5 · outbound

This paper cites Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks

Reference 70

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no resolver link, observed 2026-08-07T15:36:06.345351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:36:06.345351Z digest=sha256:a7d18d694f2cf008d2524a8a56c2f3f42dcb9a4d5ca87371ef53c5926716b936

Observation 1405ed2e-a45e-4470-84b2-701684b1d8bb · outbound

This paper cites Picle: Eliciting diverse behaviors from large language models with persona in-context learning.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Picle: Eliciting diverse behaviors from large language models with persona in-context learning

Reference 71

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unresolved
no resolver link, observed 2026-08-07T15:36:06.349742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:36:06.349742Z digest=sha256:027150c2c71b986581e7fd521836a32f09a96645ab986aca20885e207e4fc90f

Observation 5a51461d-e2dd-4efe-b594-ce34873f2643 · outbound

This paper cites Redpajama: an open dataset for training large language models, 2023.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Redpajama: an open dataset for training large language models, 2023

Reference 72

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no resolver link, observed 2026-08-07T15:36:06.352562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:36:06.352562Z digest=sha256:47ffa7fc44669e548c3185ddbd4f0e0042062f68c7652d20c38fbba747cdf36b

Observation 7413d78d-95e2-4d9f-acd9-2984b93bf6d5 · outbound

This paper cites Language Modeling Is Compression.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Language Modeling Is Compression

Reference 73

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source=arxiv_source observed=2026-08-07T15:36:06.356177Z digest=sha256:a81e491a0708537a13c90dd533f407c32ef569f17acfff6846cda5b9e3fc63b4

Observation 2ae4fb71-06e8-49bc-8eca-89de8e887beb · outbound

This paper cites A Tale of Tails: Model Collapse as a Change of Scaling Laws.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training A Tale of Tails: Model Collapse as a Change of Scaling Laws

Reference 74

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source=arxiv_source observed=2026-08-07T15:36:06.359664Z digest=sha256:c5b2e1cd1a8dc9c87d17efd8cbd1531455dbe97d80b565e1d6a3373bff141553

Observation 4faf4db1-debf-4a2f-8ddc-b2fc06b7122e · outbound

This paper cites Strategic Reasoning with Language Models.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Strategic Reasoning with Language Models

Reference 75

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source=arxiv_source observed=2026-08-07T15:36:06.362578Z digest=sha256:bfdb1d1c64d6047c9e39abf1e7d50b4d74230ef27707b66f3f086b6163febd42

Observation d726a659-b00e-4df7-aaf4-a2d1286460d4 · outbound

This paper cites In-context autoencoder for context compression in a large language model.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training In-context autoencoder for context compression in a large language model

Reference 76

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source=arxiv_source observed=2026-08-07T15:36:06.366714Z digest=sha256:612228a2fca51cdb842693a34be40340a3fc0bcc0a3e98d3cf304252c9076801

Observation b7192de9-1256-4ad8-b904-268727dd568d · outbound

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

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Measuring Mathematical Problem Solving With the MATH Dataset

Reference 77

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source=arxiv_source observed=2026-08-07T15:36:06.369829Z digest=sha256:780c1ea638f866d4549745fc4b48a2bec3ccb3f1eb7b6ba6861c641b4342e622

Observation 06432e54-e417-44d7-9902-2eb4ccfde470 · outbound

This paper cites Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning

Reference 78

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source=arxiv_source observed=2026-08-07T15:36:06.373531Z digest=sha256:38d53def639beb651072f2998b46a30a3b1be176f7869b7f8f2723c8efcc47ce

Observation 3b5bc89c-99c8-4400-b84a-031101db309c · outbound

This paper cites Faithful Persona-based Conversational Dataset Generation with Large Language Models.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Faithful Persona-based Conversational Dataset Generation with Large Language Models

Reference 79

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source=arxiv_source observed=2026-08-07T15:36:06.376808Z digest=sha256:6c44c1ca9019370f62e1dedef60f8ce3a7fc3f7d0c613f011bd795166ea089dd

Observation ee75c507-c25e-4733-9c31-0d82864e5e88 · outbound

This paper cites Scaling Laws for Neural Language Models.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Scaling Laws for Neural Language Models

Reference 80

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source=arxiv_source observed=2026-08-07T15:36:06.380190Z digest=sha256:8c15a46c0e51cba05071c4070f769871bfb52af33b64c2aaba0529f99ae12095

Observation 560a043a-ec6b-49b2-a8fe-9d6f48442fb0 · outbound

This paper cites Common 7B Language Models Already Possess Strong Math Capabilities.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Common 7B Language Models Already Possess Strong Math Capabilities

Reference 81

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source=arxiv_source observed=2026-08-07T15:36:06.383838Z digest=sha256:b75174f6360f70da72d9412aa256858bd5f5dc5054472e7209e2be6987d46f54

Observation 0fe56072-f9ae-47de-be6a-3ad2ccabe180 · outbound

This paper cites Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Reference 82

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source=arxiv_source observed=2026-08-07T15:36:06.387394Z digest=sha256:295491cba6584472a252bf09e7a7b02875313a075166a1c47ca12ba8b67da8b4

Observation 1e659dce-8972-4e91-98ea-2f1ccbee1ba5 · outbound

This paper cites On the steerability of large language models toward data-driven personas.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training On the steerability of large language models toward data-driven personas

Reference 83

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source=arxiv_source observed=2026-08-07T15:36:06.391546Z digest=sha256:51573ee2e4e039c70bf4de9505fc586e071affb057801a28a1d1b50458759a63

Observation 71e9b821-fd5c-42ee-b616-ab7b1d148288 · outbound

This paper cites Textbooks Are All You Need II: phi-1.5 technical report.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Textbooks Are All You Need II: phi-1.5 technical report

Reference 84

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source=arxiv_source observed=2026-08-07T15:36:06.394612Z digest=sha256:30ae1c974422f9b118a71032c3ad6bfa094b0b94281731dbfe85c9abfaad0739

Observation 8edad706-d3c8-40b0-8ebf-6afbea63334e · outbound

This paper cites Best Practices and Lessons Learned on Synthetic Data.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Best Practices and Lessons Learned on Synthetic Data

Reference 85

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source=arxiv_source observed=2026-08-07T15:36:06.398779Z digest=sha256:d1ec7ad8c074614374cdf08a3f6791d34bcf2dbe406edd3f6578842ffdd7b83b

Observation 9cf7383f-98b0-4199-9d5c-07e4f4053c91 · outbound

This paper cites A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration

Reference 86

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source=arxiv_source observed=2026-08-07T15:36:06.402644Z digest=sha256:0f1814d9be888153bef5f72eb125e38a69bfdbd8d6ee0307119f73b0847470f9

Observation 9f419473-e6d6-437e-a476-a105c49ab2c8 · outbound

This paper cites Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Reference 87

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source=arxiv_source observed=2026-08-07T15:36:06.407101Z digest=sha256:d5358ac1943cefd77385c0cec124b998d457893b7846dcb208f1e55f1d8ee658

Observation d04cee5b-e914-4db7-827a-78d179741f41 · outbound

This paper cites On the Risk of Misinformation Pollution with Large Language Models.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training On the Risk of Misinformation Pollution with Large Language Models

Reference 88

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source=arxiv_source observed=2026-08-07T15:36:06.410393Z digest=sha256:2c4c39f4ab6284b43fad8e23640479dd57214eb38fc0e42c268fc92a439586f1

Observation a14e6e12-d476-42c7-8230-441855efed1c · outbound

This paper cites Generative agents: Interactive simulacra of human behavior.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Generative agents: Interactive simulacra of human behavior

Reference 89

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source=arxiv_source observed=2026-08-07T15:36:06.413628Z digest=sha256:67046fbf2cff81b30b288bab9617b9f8f877d187728b0752ee3232a6bb533428

Observation 1f46e2c8-64e6-4053-893a-9ff517eac8c5 · outbound

This paper cites Toolformer: Language models can teach themselves to use tools.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Toolformer: Language models can teach themselves to use tools

Reference 90

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source=arxiv_source observed=2026-08-07T15:36:06.416532Z digest=sha256:f1217652d423d424b49c55ad09c3e7a49d415bfb36ff01a912febc80c9164cd9

Observation fd91a9fb-20eb-4044-91e3-eb6fc23421de · outbound

This paper cites Role play with large language models.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Role play with large language models

Reference 91

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source=arxiv_source observed=2026-08-07T15:36:06.420215Z digest=sha256:6a4cfb9754d1e402955438d177a0ccfc572aff216a03f40bf554675586630c2d

Observation 0096578c-eaad-445a-a237-1b52dcfc26c4 · outbound

This paper cites The Curse of Recursion: Training on Generated Data Makes Models Forget.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training The Curse of Recursion: Training on Generated Data Makes Models Forget

Reference 92

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source=arxiv_source observed=2026-08-07T15:36:06.423517Z digest=sha256:9a0d1ecb9e818e6da63d5ecdad2ed257d4115c6d0cd3c5e29eaf44afddc60d99

Observation 6391e0cf-ee5e-4b28-9c9a-685b4e98ca96 · outbound

This paper cites Introducing qwen1.5, February 2024.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Introducing qwen1.5, February 2024

Reference 93

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:36:06.427124Z digest=sha256:2266091a26a250fb58ee7b0d77ff02e139c430c0b306112cd1f2d9bcd2fd2f70

Observation f15f7804-c85e-479e-974a-1e584c3f7231 · outbound

This paper cites An experimental study of the small world problem.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training An experimental study of the small world problem

Reference 94

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raw_fallback, observed 2026-08-07T15:36:07.494829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:36:06.430052Z digest=sha256:bd0880df6ebf21e24fe87e365001b4d5d95ae936fa8724866e63484472ce0fe8

Observation 99162bc3-e811-43b2-9a9d-b354e8315ef5 · outbound

This paper cites Position: Will we run out of data? limits of llm scaling based on human-generated data.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Position: Will we run out of data? limits of llm scaling based on human-generated data

Reference 95

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source=arxiv_source observed=2026-08-07T15:36:06.433028Z digest=sha256:2449a987cfecaeefdbbb4fd34af1faf03db233d7810809f3419d62a493efc82d

Observation 9ac6abfd-775f-4358-9e43-fbd191d1ff3e · outbound

This paper cites MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning

Reference 96

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source=arxiv_source observed=2026-08-07T15:36:06.435967Z digest=sha256:b7551b932e70a82477e80a0d0981743f9e122f5d94b931f43604d9caa23c083e

Observation 9d40511d-7006-4ef1-aa8d-2ef011792d77 · outbound

This paper cites Self-Instruct: Aligning Language Models with Self-Generated Instructions.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 97

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source=arxiv_source observed=2026-08-07T15:36:06.439307Z digest=sha256:e45a815bca926c3fbabaa46bf1caf7b1e5e879f117021dd0616a5833225d0d56

Observation 4788c87d-1a02-44d3-86ac-ed09f94eb227 · outbound

This paper cites Unleashing the emergent cognitive synergy in large language models: A task-solving agent through multi-persona self-collaboration.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Unleashing the emergent cognitive synergy in large language models: A task-solving agent through multi-persona self-collaboration

Reference 98

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verified fuzzy
raw_fallback, observed 2026-08-07T15:36:07.480301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T15:36:06.442693Z digest=sha256:3b7794a4efc8516052be550709c34ae6e29107395c606d9a350e7f23bb14811f

Observation 21b16f2e-9ee1-4108-a381-27e20d616894 · outbound

This paper cites Hallucination is Inevitable: An Innate Limitation of Large Language Models.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Hallucination is Inevitable: An Innate Limitation of Large Language Models

Reference 99

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source=arxiv_source observed=2026-08-07T15:36:06.445499Z digest=sha256:8f7ca7bcdc6342ec85860a97f27ca4a5e308c973d9f429b94c41ff7d05097f5a

Observation 110233b7-af77-46b2-9ff7-b83af62e853a · outbound

This paper cites Yi: Open Foundation Models by 01.AI.

Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training Yi: Open Foundation Models by 01.AI

Reference 100

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source=arxiv_source observed=2026-08-07T15:36:06.449701Z digest=sha256:9fc90f80d5295e4daad6cb2d76e2d0cbf13ac1ebe6ef691893738c8d634e299c

Pith citing papers

Observation c96cd297-107c-456c-9eca-5663d38c3af8 · inbound

A Theory of Inference Compute Scaling: Reasoning through Directed Stochastic Skill Search cites this paper.

A Theory of Inference Compute Scaling: Reasoning through Directed Stochastic Skill Search Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training

Reference 154

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source=pdf_text observed=2026-08-07T05:07:40.131808Z digest=sha256:cbbc1cd7bbc077cedb12f388cb5995a56fe26e69454e3d64916f758fb9b9cf5d

Observation 176c6ba5-f8f2-41c5-a893-faa59179945f · inbound

Seeing but Not Thinking: Routing Distraction in Multimodal Mixture-of-Experts cites this paper.

Seeing but Not Thinking: Routing Distraction in Multimodal Mixture-of-Experts Two Experts Are All You Need for Steering Thinking: Reinforcing Cognitive Effort in MoE Reasoning Models Without Additional Training

Reference 2

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verified exact
arxiv_id, observed 2026-05-11T07:41:00.574736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-10T17:03:13.911088Z digest=sha256:47ce843f194647b7cb5c8ad419a23f517d5c7ada9bf1d431703e2adcfb12eb3f