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Paper Citation Record · LEDGER

Distilling System 2 into System 1

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 41 inbound Pith citation observations for arXiv:2407.06023.

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

pith.paper-citation-record.v1
2407.06023 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 41 of 41 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:22:33.519990Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation d0296b31-9ea9-4277-953f-9c5fa11840f0 · inbound

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

Training Large Language Models to Reason in a Continuous Latent Space Distilling System 2 into System 1

Reference 34

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arxiv_id, observed 2026-05-11T10:29:05.880354Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-11T10:29:05.384381Z digest=sha256:50b9b97b0f46c6c5b7674dacc977987db69fe843f2acbab48cbf0c9cce959d54

Observation 571742c2-1501-486e-abb1-1df06d46e972 · inbound

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

Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning Distilling System 2 into System 1

Reference 54

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source=arxiv_source observed=2026-08-09T05:22:33.519990Z digest=sha256:18fe018beee3f34051852b32fce373dc4da64f210c4859b640c29777d6ae63c0

Observation f6ce8382-113c-4c68-bdf3-562c82292451 · inbound

Syntriever: How to Train Your Retriever with Synthetic Data from LLMs cites this paper.

Syntriever: How to Train Your Retriever with Synthetic Data from LLMs Distilling System 2 into System 1

Reference 55

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source=arxiv_source observed=2026-08-09T00:40:42.654194Z digest=sha256:b0bde984e0ef9b317729baf9e5cc3a18d5b0867ab873a5e0fef6623668466714

Observation 41055a6c-f42a-4147-ae5f-31763f762d3b · inbound

Generating Symbolic World Models via Test-time Scaling of Large Language Models cites this paper.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Distilling System 2 into System 1

Reference 54

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source=pdf_text observed=2026-08-08T21:45:45.489671Z digest=sha256:cebc763af3ce141c9863008447f24aa75bf7f9fc8cfab1c7ea647b6713ee01e2

Observation 549a592e-5b9d-4877-890b-469fe03712f6 · inbound

LLM Pretraining with Continuous Concepts cites this paper.

LLM Pretraining with Continuous Concepts Distilling System 2 into System 1

Reference 25

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source=pdf_text observed=2026-08-08T04:54:39.389971Z digest=sha256:a4e4dcd466897c50e6418e8765c7a4fe47b9d496225de2867bd6ae83edc1a56b

Observation f317e0ba-ef77-4862-842e-a1745c4b7ee3 · inbound

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

CoT-Valve: Length-Compressible Chain-of-Thought Tuning Distilling System 2 into System 1

Reference 44

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source=arxiv_source observed=2026-08-07T20:57:42.151798Z digest=sha256:0549d254d75617639c31a7e8c6d5920e4e9f90a30064b75de64cb203bfce822e

Observation 9b38c22c-8819-4640-af25-987a46cb3dd8 · 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 Distilling System 2 into System 1

Reference 219

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-14T01:29:56.480020Z digest=sha256:fd82b6deabfe9f3f084e1687bb230e6b6e14fec03ec8e9f6f1000ec28e926e93

Observation fe40850a-91f5-4aae-a544-28358b2e109e · inbound

Don't "Overthink" Passage Reranking: Is Reasoning Truly Necessary? cites this paper.

Don't "Overthink" Passage Reranking: Is Reasoning Truly Necessary? Distilling System 2 into System 1

Reference 29

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source=arxiv_source observed=2026-08-07T14:54:54.608108Z digest=sha256:e1f0675fd42d98f12e28d717e51e69eb35c37bebbe5703402652194646d2a3fa

Observation b9d9b461-877f-440b-b121-35c986759125 · inbound

TrimR: Verifier-based Training-Free Thinking Compression for Efficient Test-Time Scaling cites this paper.

TrimR: Verifier-based Training-Free Thinking Compression for Efficient Test-Time Scaling Distilling System 2 into System 1

Reference 34

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source=pdf_text observed=2026-08-07T15:00:39.276955Z digest=sha256:b7ff0b03efb1298819073fc508f93ca9730e129e9e394227fb1eec99b9878007

Observation d19e77e3-b165-4f9c-935d-a732ad3f57ad · inbound

Activation Control for Efficiently Eliciting Long Chain-of-thought Ability of Language Models cites this paper.

Activation Control for Efficiently Eliciting Long Chain-of-thought Ability of Language Models Distilling System 2 into System 1

Reference 8

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source=pdf_text observed=2026-08-07T14:46:13.808759Z digest=sha256:dbe2aee647f6671809f88a14748630c720362d9b19baf09e086c66e2ae1c3fb6

Observation 62de50e9-0453-41e0-a8c4-02ca38158211 · inbound

TAG-INSTRUCT: Controlled Instruction Complexity Enhancement through Structure-based Augmentation cites this paper.

TAG-INSTRUCT: Controlled Instruction Complexity Enhancement through Structure-based Augmentation Distilling System 2 into System 1

Reference 8

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source=pdf_text observed=2026-08-07T14:32:14.018366Z digest=sha256:fd0fc70a6fd5a035e09a9a449204efbf3566620e7fc17e3af8611010ff72460c

Observation 526186fb-c4d5-4067-ba39-13d1810f9399 · inbound

System-1.5 Reasoning: Traversal in Language and Latent Spaces with Dynamic Shortcuts cites this paper.

System-1.5 Reasoning: Traversal in Language and Latent Spaces with Dynamic Shortcuts Distilling System 2 into System 1

Reference 53

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source=pdf_text observed=2026-08-07T14:27:40.768478Z digest=sha256:3d75e8aba2ef3ce51e49a96ca9e9b407fce6e62f1ac3b9d558d7960b38b8a7e3

Observation 80ed8408-4f5a-411a-bc92-c88d7f54a7f1 · inbound

Self-Route: Automatic Mode Switching via Capability Estimation for Efficient Reasoning cites this paper.

Self-Route: Automatic Mode Switching via Capability Estimation for Efficient Reasoning Distilling System 2 into System 1

Reference 34

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source=arxiv_source observed=2026-08-07T13:54:28.144052Z digest=sha256:de7a65b1ca6e97637fccc48f43a843e3068631e083d7fb0b052e3d0068cdb30a

Observation 8f8a18ce-6d25-460e-9e8c-44180ee4edb5 · inbound

Pangu Embedded: An Efficient Dual-system LLM Reasoner with Metacognition cites this paper.

Pangu Embedded: An Efficient Dual-system LLM Reasoner with Metacognition Distilling System 2 into System 1

Reference 56

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source=pdf_text observed=2026-08-07T13:16:17.920572Z digest=sha256:14f08b2a407eb4e0a7512861237c1c6241f3512b1e5b05b7125ac9b8bf4f79a9

Observation b5fa618f-c3e6-485a-a7ff-a31966b3128f · inbound

Integrating Neural and Symbolic Components in a Model of Pragmatic Question-Answering cites this paper.

Integrating Neural and Symbolic Components in a Model of Pragmatic Question-Answering Distilling System 2 into System 1

Reference 50

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source=arxiv_source observed=2026-08-07T11:47:50.103706Z digest=sha256:a9de55955947826a741a98efd993370703be0909322a46ff196e137419abb03b

Observation fd60d37c-3213-4e06-b499-7b1b6659cc6e · inbound

What makes Reasoning Models Different? Follow the Reasoning Leader for Efficient Decoding cites this paper.

What makes Reasoning Models Different? Follow the Reasoning Leader for Efficient Decoding Distilling System 2 into System 1

Reference 75

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source=pdf_text observed=2026-08-07T05:52:18.741862Z digest=sha256:88afd073ff2acd9d110ede00e4dbceaf933df195e4a5d6835b694cf1fafc72ef

Observation 3def0778-7059-489c-b93e-13253303564e · inbound

How Far Are We from Optimal Reasoning Efficiency? cites this paper.

How Far Are We from Optimal Reasoning Efficiency? Distilling System 2 into System 1

Reference 54

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source=pdf_text observed=2026-08-07T05:49:40.051297Z digest=sha256:b4c71f7bd73b2c3aa4b7515210e87ab7a69e95e25cac033ea8487ab866086876

Observation bc454bb5-6bd7-4bab-991f-a9323952bf34 · inbound

ETA: Efficiency through Thinking Ahead, A Dual Approach to Self-Driving with Large Models cites this paper.

ETA: Efficiency through Thinking Ahead, A Dual Approach to Self-Driving with Large Models Distilling System 2 into System 1

Reference 40

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source=pdf_text observed=2026-08-07T05:32:32.730908Z digest=sha256:1d8a459af97e16b05aed1df67fa674ee700a7108c2101090a0b8f4447ab63803

Observation 6acec992-b6e4-455d-aea0-946386f837f9 · inbound

Wait, We Don't Need to "Wait"! Removing Thinking Tokens Improves Reasoning Efficiency cites this paper.

Wait, We Don't Need to "Wait"! Removing Thinking Tokens Improves Reasoning Efficiency Distilling System 2 into System 1

Reference 49

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source=arxiv_source observed=2026-08-07T05:19:19.780072Z digest=sha256:6bfdda642d021e2855ff8841c3bdb1a3b1b093444ec8aa74c61a8a41eb1a777b

Observation 39688aed-efff-45b7-ad48-e0800b7fd641 · inbound

Optimizing Length Compression in Large Reasoning Models cites this paper.

Optimizing Length Compression in Large Reasoning Models Distilling System 2 into System 1

Reference 35

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source=arxiv_source observed=2026-08-07T00:16:40.762333Z digest=sha256:5a6e3be0837721ac413b6c17e4fbc375bcce59d54075d9f3433241723210c129

Observation e70b2234-1390-42a5-bbde-9a331c05bdb6 · inbound

Do Thinking Tokens Help or Trap? Towards More Efficient Large Reasoning Model cites this paper.

Do Thinking Tokens Help or Trap? Towards More Efficient Large Reasoning Model Distilling System 2 into System 1

Reference 48

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source=arxiv_source observed=2026-08-06T21:45:11.449407Z digest=sha256:93ab666cffd6c7a19a38397213d44aff466690d015955da6e91999c319ee6daf

Observation 1dbe3125-988b-4e6a-bd9f-40f3ae4d189f · inbound

NaturalThoughts: Selecting and Distilling Reasoning Traces for General Reasoning Tasks cites this paper.

NaturalThoughts: Selecting and Distilling Reasoning Traces for General Reasoning Tasks Distilling System 2 into System 1

Reference 28

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source=arxiv_source observed=2026-08-06T20:43:26.226686Z digest=sha256:a6742e85adc72ab7b3abc4db231b65ac6efe9b56f2381045f5b1fda394ed6e27

Observation 39542602-6445-4595-8bf8-8aea9305df13 · inbound

Reasoning on a Budget: A Survey of Adaptive and Controllable Test-Time Compute in LLMs cites this paper.

Reasoning on a Budget: A Survey of Adaptive and Controllable Test-Time Compute in LLMs Distilling System 2 into System 1

Reference 34

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source=pdf_text observed=2026-08-06T20:43:10.962760Z digest=sha256:c47672a3f4c88f4a67d781227ccbb083bdc9cf18ebb25260926a0af8fad734b8

Observation 39a07db6-59ba-46b2-bdf6-68f091aca571 · 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 Distilling System 2 into System 1

Reference 231

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source=arxiv_source observed=2026-08-06T17:54:18.017105Z digest=sha256:19252d10f6986e9aa41295a8dc44918b76136f49d1f83d8a6c9ff4058316dd95

Observation a7834192-50b9-4a2c-a1b0-fab71059e897 · inbound

KRETA: A Benchmark for Korean Reading and Reasoning in Text-Rich VQA Attuned to Diverse Visual Contexts cites this paper.

KRETA: A Benchmark for Korean Reading and Reasoning in Text-Rich VQA Attuned to Diverse Visual Contexts Distilling System 2 into System 1

Reference 1

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source=pdf_text observed=2026-08-05T15:23:54.147498Z digest=sha256:3d8f461cc405f0feb12ddf1774c26b20d7ae5012f6de8b25dc20d55f2c2aa391

Observation 43e062bc-429b-40ba-8370-a5ac53c265a7 · inbound

Self-Aligned Reward: Towards Effective and Efficient Reasoners cites this paper.

Self-Aligned Reward: Towards Effective and Efficient Reasoners Distilling System 2 into System 1

Reference 51

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arxiv_id, observed 2026-05-18T18:31:44.655448Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-18T18:27:23.076544Z digest=sha256:c1f6c748a3a0dd42cfe8e3c4a0fa68df0bcecca9e506866f530ea04669b9fd53

Observation f927999e-026d-4937-b922-99776b2db7c9 · inbound

From Long to Short: LLMs Excel at Trimming Own Reasoning Chains cites this paper.

From Long to Short: LLMs Excel at Trimming Own Reasoning Chains Distilling System 2 into System 1

Reference 51

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source=pdf_text observed=2026-08-05T00:04:02.808372Z digest=sha256:3cacd2053658fe0a6d8eec5b87b512ff56f651d6ee3c264f131606ae4039f321

Observation 48385763-2175-4e14-9323-4497471d0130 · inbound

Are Large Reasoning Models Interruptible? cites this paper.

Are Large Reasoning Models Interruptible? Distilling System 2 into System 1

Reference 33

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source=arxiv_source observed=2026-08-04T10:07:53.199815Z digest=sha256:21d4b5824b75f642632dee517f6ffd7a747b4d722143cb4170e741bd6329387c

Observation 02432e68-6d9a-4954-bab6-47cd1fb8144e · inbound

Physics of Language Models: Part 4.1, Architecture Design and the Magic of Canon Layers cites this paper.

Physics of Language Models: Part 4.1, Architecture Design and the Magic of Canon Layers Distilling System 2 into System 1

Reference 77

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source=pdf_text observed=2026-08-03T15:22:55.850040Z digest=sha256:70a91823167e22bdbb57aeb65691a70f6148782328429fa167eea878a3226404

Observation f82664c5-fca8-432c-947b-5c835aa8432d · inbound

Neural Chain-of-Thought Search: Searching the Optimal Reasoning Path to Enhance Large Language Models cites this paper.

Neural Chain-of-Thought Search: Searching the Optimal Reasoning Path to Enhance Large Language Models Distilling System 2 into System 1

Reference 14

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arxiv_id, observed 2026-05-16T13:22:55.281813Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T13:21:36.606855Z digest=sha256:50ab84d4510ff472f06305fd31892468f07ed9278026aa62af99d7bfd5e090f0

Observation 8771343a-b51e-48b9-bf6f-2306090d5c72 · inbound

Skill-SD: Skill-Conditioned Self-Distillation for Multi-turn LLM Agents cites this paper.

Skill-SD: Skill-Conditioned Self-Distillation for Multi-turn LLM Agents Distilling System 2 into System 1

Reference 42

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arxiv_id, observed 2026-05-11T10:31:00.972000Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T15:28:07.981488Z digest=sha256:f5d95cb10019712e1f3dace124ba774f6e215bb80fcedd9053df6de5c568d5da

Observation 0f87114f-ac6a-4a33-93e6-f8b1b7e76baa · inbound

Efficient Test-Time Scaling via Temporal Reasoning Aggregation cites this paper.

Efficient Test-Time Scaling via Temporal Reasoning Aggregation Distilling System 2 into System 1

Reference 20

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arxiv_id, observed 2026-05-10T06:21:27.016232Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T06:17:17.129840Z digest=sha256:fc7291a63c883d067cc4f5df9258126b4d81b7ca81191e24bdabbd56a1b92b48

Observation 112b5da3-44b5-47f0-92a4-62539fbbfc51 · inbound

Knowledge Distillation Must Account for What It Loses cites this paper.

Knowledge Distillation Must Account for What It Loses Distilling System 2 into System 1

Reference 36

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arxiv_id, observed 2026-05-11T23:26:17.952686Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T16:58:41.449172Z digest=sha256:abd6de8657ff7e174a2f113f429477e1657e8b03ebb2c04191853cd817b167af

Observation f97df7be-c3d1-44a1-8a30-0992a92516cb · inbound

Knowledge Distillation Must Account for What It Loses cites this paper.

Knowledge Distillation Must Account for What It Loses Distilling System 2 into System 1

Reference 36

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arxiv_id, observed 2026-05-11T22:01:13.573826Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T03:31:56.787201Z digest=sha256:758b7778ebbbec88eedc11347da48282c7d19764c982920ad4c8fb1b32a59fb1

Observation 7275a523-2417-4956-a186-1d60a37da73d · 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 Distilling System 2 into System 1

Reference 58

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arxiv_id, observed 2026-05-11T20:06:09.050599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-08T10:19:08.451445Z digest=sha256:85636849223886814727d93bcd7df61ee88a7838e6f9e3306d9dbaea33268a6a

Observation 9e0e68b6-7c2d-4948-b2d6-26165f8fe510 · inbound

NoisyCoconut: Counterfactual Consensus via Latent Space Reasoning cites this paper.

NoisyCoconut: Counterfactual Consensus via Latent Space Reasoning Distilling System 2 into System 1

Reference 53

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arxiv_id, observed 2026-05-12T08:41:24.454079Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-12T00:51:40.815981Z digest=sha256:a6d46dbf741fe3706077ab6bd38c043533eb0feba32b4fd8f39ff6a2758328a6

Observation 465725f1-26d7-4222-91bd-8585078bb725 · inbound

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning cites this paper.

ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning Distilling System 2 into System 1

Reference 35

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verified exact
arxiv_id, observed 2026-07-02T03:26:28.717125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T10:07:16.700499Z digest=sha256:63d6029cdc04219b93b7cb689f86394b5f9b56d673c11aa44af12d83ea7d8f45

Observation b962f982-3edd-4d66-9356-c796f94b344b · inbound

Dynamic Rollout Editing for Reducing Overthinking in RL-Trained Reasoning Models cites this paper.

Dynamic Rollout Editing for Reducing Overthinking in RL-Trained Reasoning Models Distilling System 2 into System 1

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-06-27T01:20:20.448324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T01:19:55.164835Z digest=sha256:c097cfa26b6538eb1821529f05f56a79aef53e54bbee22eb1a849268d4503499

Observation d8861a76-bd92-477a-9b73-36a72700a02d · inbound

E-TTS: A New Embodied Test-Time Scaling Framework for Robotic Manipulation cites this paper.

E-TTS: A New Embodied Test-Time Scaling Framework for Robotic Manipulation Distilling System 2 into System 1

Reference 44

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T13:59:51.744502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T04:48:28.868562Z digest=sha256:860cf09018b0d204c504b4f405e25de09d0f8582ef2205ffe7a57ef5f8b03c86

Observation 168b237d-252b-4408-a5a0-94405db34aa0 · inbound

Purified OPSD: On-Policy Self-Distillation Without Losing How to Think cites this paper.

Purified OPSD: On-Policy Self-Distillation Without Losing How to Think Distilling System 2 into System 1

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-07-03T13:58:21.037500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-03T13:56:13.827493Z digest=sha256:5f5b389b218cf5a78f8a1eab43f3a92b306798a2cca83532ffe44c392d8bb5cc

Observation 5cf5d0e1-aba5-4bf6-8dc3-69080df4f225 · inbound

CritiqueDriveVLM: From Verifier-Guided Reinforcement Learning to Latent Thought Distillation for Autonomous Driving cites this paper.

CritiqueDriveVLM: From Verifier-Guided Reinforcement Learning to Latent Thought Distillation for Autonomous Driving Distilling System 2 into System 1

Reference 61

Resolution
unresolved
no resolver link, observed 2026-07-11T21:09:01.431209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:09:01.431209Z digest=sha256:aa90580fccdebef66b4d87d714cb80fdc1198604c5b47b1e09f84e907b4221be