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Paper Citation Record · LEDGER

Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 37 inbound Pith citation observations for arXiv:2412.09078.

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

pith.paper-citation-record.v1
2412.09078 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 37 of 37 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 37 of 37 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T16:35:28.392673Z

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 9f9b5af0-f6c9-4a12-b53c-52a27ba770c1 · inbound

Large Language Model-Enhanced Multi-Armed Bandits cites this paper.

Large Language Model-Enhanced Multi-Armed Bandits Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 2016

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no resolver link, observed 2026-08-09T16:35:28.392673Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:35:28.392673Z digest=sha256:76ae118399f94887acd063a99c254d5ad3a2fa42870492bdd2f36b660a6ed6a1

Observation ffc22cfc-2155-4245-a301-e534e4828c14 · inbound

Typhoon T1: An Open Thai Reasoning Model cites this paper.

Typhoon T1: An Open Thai Reasoning Model Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 9

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no resolver link, observed 2026-08-07T22:52:54.274766Z

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source=arxiv_source observed=2026-08-07T22:52:54.274766Z digest=sha256:fd9d75b9a37fe4879fff8f550fbe1f8f429cd4e81a650f361ffe423e3220e5f8

Observation 0d022c3a-287a-4c10-8a86-5da465749e62 · inbound

From System 1 to System 2: A Survey of Reasoning Large Language Models cites this paper.

From System 1 to System 2: A Survey of Reasoning Large Language Models Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 127

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arxiv_id, observed 2026-05-13T01:36:24.046281Z

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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=2026-05-13T01:36:23.845366Z digest=sha256:f2917dedb4782067bd13cecc8c98696c88ada56d096701d696f1f05502541dbf

Observation 654d0e28-ee02-46d6-bf59-4075ae6ae759 · inbound

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

Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 56

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arxiv_id, observed 2026-05-12T08:40:41.217213Z

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=2026-05-12T08:40:40.910461Z digest=sha256:1618aaabba854eef2900d0215b9f10a5723b3cdce4b5889d870f35d40a951159

Observation 32dce7d0-3732-49e0-a823-982c27e6e566 · inbound

ThinkLess: A Training-Free Inference-Efficient Method for Reducing Reasoning Redundancy cites this paper.

ThinkLess: A Training-Free Inference-Efficient Method for Reducing Reasoning Redundancy Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 4

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no resolver link, observed 2026-08-07T15:17:49.984575Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:17:49.984575Z digest=sha256:5e22ea2e7c6aead9fd797a992e74e2a4c9d1bd99efa332d3e5cf728bf5439029

Observation 3cd8eca1-6f16-40de-8924-1cde0459efd7 · inbound

MARCO: Meta-Reflection with Cross-Referencing for Code Reasoning cites this paper.

MARCO: Meta-Reflection with Cross-Referencing for Code Reasoning Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 7

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source=pdf_text observed=2026-08-07T14:49:28.072575Z digest=sha256:05969c3618916cbbc9d64a37d13f3f01d4dfdda8b389797346db9aec81cea368

Observation 8198a83c-174c-47bb-9380-71fc6c8467c9 · inbound

Stepwise Reasoning Checkpoint Analysis: A Test Time Scaling Method to Enhance LLMs' Reasoning cites this paper.

Stepwise Reasoning Checkpoint Analysis: A Test Time Scaling Method to Enhance LLMs' Reasoning Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 3

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source=arxiv_source observed=2026-08-07T14:45:15.995858Z digest=sha256:64e39f136bb4b6c7ccb143b21e580a9537fe8f19d5f8c3fc4e92de226edb5d81

Observation 55382d2e-56fb-42ba-b726-b33408344093 · inbound

Think Again! The Effect of Test-Time Compute on Preferences, Opinions, and Beliefs of Large Language Models cites this paper.

Think Again! The Effect of Test-Time Compute on Preferences, Opinions, and Beliefs of Large Language Models Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 5

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source=arxiv_source observed=2026-08-07T14:14:40.097621Z digest=sha256:46717a0e819add20216e0b69903c44a1ac7a0a96d6b2852094a6f8cb4b25d92c

Observation d888a5bc-173e-4cac-98e9-514556a83858 · inbound

AutoChemSchematic AI: Agentic Physics-Aware Automation for Chemical Manufacturing Scale-Up cites this paper.

AutoChemSchematic AI: Agentic Physics-Aware Automation for Chemical Manufacturing Scale-Up Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 4

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no resolver link, observed 2026-08-07T12:35:26.079482Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:35:26.079482Z digest=sha256:da566e2364b5bd19be56e5d4627fc7f2b86501136185950fc223f4099a807146

Observation f0b24b53-ce89-4eeb-8b57-0b237e83940b · inbound

Subspace Networks: Scaling Decentralized Training with Communication-Efficient Model Parallelism cites this paper.

Subspace Networks: Scaling Decentralized Training with Communication-Efficient Model Parallelism Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 5

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source=arxiv_source observed=2026-08-07T11:55:12.978236Z digest=sha256:0a26624b002696659a20f97bd3492f21ef8cadca2aea2426ac5012d2fd293303

Observation f8e87d75-e03e-4ac8-9359-e921fa81b7d9 · inbound

Structured Pruning for Diverse Best-of-N Reasoning Optimization cites this paper.

Structured Pruning for Diverse Best-of-N Reasoning Optimization Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 7

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:56:23.527265Z digest=sha256:20e046a70d06413778b5739741bd2b14011bec3c35dc8e261eb3dd4efba0744c

Observation f5be3e27-449a-4cd6-81b7-0ce34f474c07 · inbound

Revisiting Test-Time Scaling: A Survey and a Diversity-Aware Method for Efficient Reasoning cites this paper.

Revisiting Test-Time Scaling: A Survey and a Diversity-Aware Method for Efficient Reasoning Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 4

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no resolver link, observed 2026-08-07T10:42:38.180338Z

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source=arxiv_source observed=2026-08-07T10:42:38.180338Z digest=sha256:a13850ac53d561a7d1e39451cf447392b31abb0036ef82b42c69c258b0e8d272

Observation f1f9db60-bd9f-4878-91fa-1e2ff7dd681a · inbound

LLM-First Search: Self-Guided Exploration of the Solution Space cites this paper.

LLM-First Search: Self-Guided Exploration of the Solution Space Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 52

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source=pdf_text observed=2026-08-07T10:28:46.383365Z digest=sha256:ac92087aa72365115e4ac1b132934fac3cf237e0de61d39bf390543605d7d488

Observation 18dedfcc-cf37-4917-9de4-ba0fdaf51c54 · inbound

CyberV: Cybernetics for Test-time Scaling in Video Understanding cites this paper.

CyberV: Cybernetics for Test-time Scaling in Video Understanding Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 6

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no resolver link, observed 2026-08-07T05:26:47.019699Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:26:47.019699Z digest=sha256:80ab98279deed7036b8a58f9da4a4c08936ebe7883d819b517e4bae1b1eb0ed2

Observation d7f4873e-9094-4262-84c6-2291596e9148 · inbound

A Survey on Large Language Models for Mathematical Reasoning cites this paper.

A Survey on Large Language Models for Mathematical Reasoning Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 11

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no resolver link, observed 2026-08-07T05:14:44.763862Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:44.763862Z digest=sha256:67aee743a90ab6d3fac9094b0137c506e8b883c8e0bd0fa990ccb5779025e90a

Observation b7e8f173-a84d-4a68-85be-f207b761ac40 · inbound

DenseWorld-1M: Towards Detailed Dense Grounded Caption in the Real World cites this paper.

DenseWorld-1M: Towards Detailed Dense Grounded Caption in the Real World Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 2

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no resolver link, observed 2026-08-06T21:27:37.800973Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:27:37.800973Z digest=sha256:b0d7bea677e941e52540ca7ab1725b265094ea78b179923d3c4c61e1f223bca5

Observation 2834e64d-6ec3-411c-9030-a249492e2821 · inbound

Bottom-up Domain-specific Superintelligence: A Reliable Knowledge Graph is What We Need cites this paper.

Bottom-up Domain-specific Superintelligence: A Reliable Knowledge Graph is What We Need Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 105

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no resolver link, observed 2026-08-06T16:17:43.991573Z

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source=pdf_text observed=2026-08-06T16:17:43.991573Z digest=sha256:671816e03bd806791d92b2b06df4b32ebf5e3616228ff2edb506ed6ae58ace6d

Observation c26ef4ec-e54a-403d-9a3e-d34b11adfc6a · inbound

A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence cites this paper.

A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 168

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arxiv_id, observed 2026-05-14T22:23:14.933529Z

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=2026-05-14T22:23:14.621091Z digest=sha256:706c4f32fe885ee2042105eeaf0a83663bddc13acee613aea9e3c1d5e1c403e5

Observation 360e783b-fbb5-4efe-913f-ea5d6a947d32 · inbound

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs cites this paper.

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 2024

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no resolver link, observed 2026-08-04T23:56:34.869231Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:56:34.869231Z digest=sha256:de81b0a94be9c29863035ffeb7f10a636aeba149df5274dabd65ef39a9d1c4f4

Observation d3e073bd-3845-4f63-b509-d082f46bf6f7 · inbound

Explicit Reasoning Makes Better Judges: A Systematic Study on Accuracy, Efficiency, and Robustness cites this paper.

Explicit Reasoning Makes Better Judges: A Systematic Study on Accuracy, Efficiency, and Robustness Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 34

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arxiv_id, observed 2026-05-18T17:31:41.505306Z

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=2026-05-18T17:31:28.644151Z digest=sha256:3d197b16eea3959b4d90d73eabb9ae6572440b9b8827770d5e6d3ec1efc3cd17

Observation f5f82a41-8ee9-44ae-86b6-ccc2a3aec38a · inbound

DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search cites this paper.

DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 3

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arxiv_id, observed 2026-05-18T12:12:35.836909Z

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=2026-05-18T12:12:25.437344Z digest=sha256:c6e40e220a8f85abd0deff8edde0c5b8c987e365c665a05fbfbf2d5a4d71e401

Observation f65e2b77-d569-4f48-b587-ae48707b89e7 · inbound

Self-Reflective Generation at Test Time cites this paper.

Self-Reflective Generation at Test Time Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 3

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no resolver link, observed 2026-08-04T12:41:42.303969Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T12:41:42.303969Z digest=sha256:a696dcbcf024fcf8752a85b9778f2151f3c51ef93f8dab5cc3911e871cbdcbc6

Observation 3a3df5fd-f02c-4356-bca2-1dc717c278db · inbound

Less Diverse, Less Safe: The Indirect But Pervasive Risk of Test-Time Scaling in Large Language Models cites this paper.

Less Diverse, Less Safe: The Indirect But Pervasive Risk of Test-Time Scaling in Large Language Models Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 11

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arxiv_id, observed 2026-05-18T09:56:13.113998Z

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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=2026-05-18T09:53:57.765473Z digest=sha256:1f557ba1aacc93cf33625dd413a52a849c9459ba5932ecd74ba2fafd9f225015

Observation e90d3606-b78c-489a-81de-17a3eeb9a798 · inbound

Re-FORC: Adaptive Reward Prediction for Efficient Chain-of-Thought Reasoning cites this paper.

Re-FORC: Adaptive Reward Prediction for Efficient Chain-of-Thought Reasoning Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 27

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source=pdf_text observed=2026-08-04T00:18:52.530409Z digest=sha256:5b345d466f06de260617e56be653d17f7515846e69058d26fcbee2d24ae4e619

Observation 3d2ac0bf-b775-47b6-b766-fa0590755ef2 · inbound

CLEANER: Self-Purified Trajectories Boost Agentic Reinforcement Learning cites this paper.

CLEANER: Self-Purified Trajectories Boost Agentic Reinforcement Learning Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 2024

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no resolver link, observed 2026-08-03T09:01:48.241440Z

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source=pdf_text observed=2026-08-03T09:01:48.241440Z digest=sha256:aacdfe2713992806ff79938f601dff51b2d3671e10bc1365132f13fe652acc36

Observation 1ffd052d-2e26-4db3-af79-49bbabbb687b · inbound

Framework of Thoughts: A Foundation Framework for Dynamic and Optimized Reasoning based on Chains, Trees, and Graphs cites this paper.

Framework of Thoughts: A Foundation Framework for Dynamic and Optimized Reasoning based on Chains, Trees, and Graphs Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 5

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no resolver link, observed 2026-08-02T22:33:34.383148Z

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source=arxiv_source observed=2026-08-02T22:33:34.383148Z digest=sha256:eafb0a8815b2f3ee2806144e1d73ed046e85fd583905a3609e93127ada702692

Observation 8855ea0c-71e9-4f05-a63b-424eef1d3648 · inbound

GroupRAG: Cognitively Inspired Group-Aware Retrieval and Reasoning via Knowledge-Driven Problem Structuring cites this paper.

GroupRAG: Cognitively Inspired Group-Aware Retrieval and Reasoning via Knowledge-Driven Problem Structuring Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 2013

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source=pdf_text observed=2026-08-02T17:29:45.196278Z digest=sha256:f9cad33ea8c7c5e769575c8fb03b56f2ba3440dbc4e9bc5c20f5675bf5dd8707

Observation 289b28a3-a206-457f-b959-1ee7185a0a2e · inbound

TDA-RC: Task-Driven Alignment for Knowledge-Based Reasoning Chains in Large Language Models cites this paper.

TDA-RC: Task-Driven Alignment for Knowledge-Based Reasoning Chains in Large Language Models Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 44

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verified exact
arxiv_id, observed 2026-05-15T12:25:35.930889Z

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=2026-05-15T12:21:39.237267Z digest=sha256:8198b57392b3d974fbe6c6576bfee6257081dda49d8ec14f2c2373073091be0d

Observation eade4b83-618a-4a13-bd6d-1a80bf5e83d1 · inbound

Hive: A Multi-Agent Infrastructure for Algorithm- and Task-Level Scaling cites this paper.

Hive: A Multi-Agent Infrastructure for Algorithm- and Task-Level Scaling Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 4

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arxiv_id, observed 2026-05-10T06:36:36.679394Z

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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=2026-05-10T06:31:36.776819Z digest=sha256:e78d56f421460c73f8c30c7ee95d646a6a321039b67b70010c812c8e44aa7689

Observation 34b2ff66-164d-42a4-b10c-836ec9b5cca5 · inbound

When to Vote, When to Rewrite: Disagreement-Guided Strategy Routing for Test-Time Scaling cites this paper.

When to Vote, When to Rewrite: Disagreement-Guided Strategy Routing for Test-Time Scaling Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 4

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verified exact
arxiv_id, observed 2026-05-12T09:26:25.720376Z

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=2026-05-07T11:00:21.413246Z digest=sha256:dba096463f96ca24d1f66a04897adaf0c4388c33aa0e5f181897576165cbc329

Observation 1e0a8e95-9b44-46b0-ba51-97c4f94be4b9 · inbound

When to Vote, When to Rewrite: Disagreement-Guided Strategy Routing for Test-Time Scaling cites this paper.

When to Vote, When to Rewrite: Disagreement-Guided Strategy Routing for Test-Time Scaling Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 4

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no resolver link, observed 2026-08-04T05:23:27.111986Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:23:27.111986Z digest=sha256:bec55bba4304720f7bd7444dfc198ba3e91e11a64f6463c3971ffe3af5476709

Observation 691f4b76-8c48-4a25-a80b-3fd7c811ac2a · inbound

Confidence-Aware Alignment Makes Reasoning LLMs More Reliable cites this paper.

Confidence-Aware Alignment Makes Reasoning LLMs More Reliable Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 3

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arxiv_id, observed 2026-05-11T03:55:54.065259Z

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=2026-05-11T02:10:40.020460Z digest=sha256:6eb9ac122ccb89c894e993c11d3786fb4996cbbbecceb6fa4cb5a2acc499d634

Observation 74c6b7b8-962e-44c4-adb6-0c703a9cd035 · inbound

Exploiting Verification-Generation Gap: Test-Time Reinforcement Learning with Confidence-Conditioned Verification cites this paper.

Exploiting Verification-Generation Gap: Test-Time Reinforcement Learning with Confidence-Conditioned Verification Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 21

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arxiv_id, observed 2026-07-02T02:26:27.239258Z

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=2026-06-28T10:53:00.223228Z digest=sha256:386efb1281b8db84f98a9a863efec58087dc675d6cd55c99d7c5b62afef10fb3

Observation cf632ae4-b2ce-4acc-94d3-e9ca3a990c66 · inbound

KCSAT-ML: Probing Reasoning Models with Nationwide-Cohort Human Difficulty cites this paper.

KCSAT-ML: Probing Reasoning Models with Nationwide-Cohort Human Difficulty Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-06-27T13:10:55.961429Z

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=2026-06-27T13:07:59.509660Z digest=sha256:b862f8c204c189bf607ceb7812c460df1c91a25d4038fedf5d387802132283f5

Observation ef5e49f5-19db-459d-a60f-6508dae509be · inbound

DIRECT: When and Where Should You Allocate Test-Time Compute in Embodied Planners? cites this paper.

DIRECT: When and Where Should You Allocate Test-Time Compute in Embodied Planners? Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-07-03T11:08:03.069720Z

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=2026-06-27T09:42:17.813126Z digest=sha256:cc6a00940bb26759615799ce434c7b9817fcc7b4f506eba8a4da703ced1b7027

Observation 116acd43-21e2-4912-b415-f993d19b8c38 · inbound

MetaPS: Adaptive Programmatic Strategy Selection for Market Agents cites this paper.

MetaPS: Adaptive Programmatic Strategy Selection for Market Agents Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 121

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T08:39:42.714748Z

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=2026-06-26T11:06:28.690956Z digest=sha256:0a36f69b973d9cfe5ca959570c65495e89059895eeadaff312d34c9284830f0e

Observation 664bcbc4-8357-4e78-ba16-75556ad21786 · inbound

Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy cites this paper.

Enhancing SLMs for Sustainable Code Optimization in Radio-Astronomy Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-01T08:18:31.256413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T08:18:31.256413Z digest=sha256:be75b705314f8ea6a2fbd17c79868cc7a62f006ca4caf592384373ecc65b94fd