Pith. sign in

Paper Citation Record · LEDGER

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks

As of 10 August 2026, this Paper Citation Record lists 95 of 95 outbound references and 4 inbound Pith citation observations for arXiv:2501.10069.

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

pith.paper-citation-record.v1
2501.10069 v4

Coverage vector

measured 95 of 95 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:27:23.569311Z

measured 99 of 99 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T16:18:40.793196Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T08:09:40.660151Z

Reference resolution

95 of 95 outbound references displayed

  • verified exact2
  • verified fuzzy33
  • unresolved59
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4a9b394b-49a6-47d1-828a-48d8980272ff · outbound

This paper cites GPT-4 Technical Report.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks GPT-4 Technical Report

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.237635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.237635Z digest=sha256:3a33bdcd223a29a7d04f4a4f344c71f2e834a62bf5b53a5e635532b643abc1c8

Observation f3703b83-bdd5-42bd-affb-6edec0889a10 · outbound

This paper cites Program Synthesis with Large Language Models.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Program Synthesis with Large Language Models

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.242706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.242706Z digest=sha256:e921e82b18292084110adafb13f45cce6c9948a9fcd77451bcdd4eb9a7a330f7

Observation 84a8036c-d776-49c6-b07e-15860daf78bb · outbound

This paper cites Dynamic programming.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Dynamic programming

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.247120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.247120Z digest=sha256:509a030bba1e6ab2013ee759eb8c7daa6819d4bac9ac8921d8433322d13e8be4

Observation de9c7c5a-e8a1-4a6a-8067-f318a44238c7 · outbound

This paper cites Graph of thoughts: Solving elaborate problems with large language models.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Graph of thoughts: Solving elaborate problems with large language models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.250993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.250993Z digest=sha256:b1935f32d958dfd8cd56b76a8094614cd00e2958b58716261f731de36c2fd4d4

Observation c7283b02-0152-4810-87f8-3675ca982b1e · outbound

This paper cites Navigating the labyrinth: Evaluating and enhancing LLM s ability to reason about search problems, 2024.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Navigating the labyrinth: Evaluating and enhancing LLM s ability to reason about search problems, 2024

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.254855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.254855Z digest=sha256:903a5c16908fdb3c25c903f98e8a84a8784d6201cc7deda92e9e1c47d36071d7

Observation 703ab644-0e19-4c31-aaa1-3393c278679b · outbound

This paper cites Language models are few-shot learners.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Language models are few-shot learners

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.258541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.258541Z digest=sha256:36238e6a5bad622a3fbc9ba5037d6b83170efd3f53f608a0270cdc4a0f89a50b

Observation 4c28d59d-2473-4dd9-b7b5-14d098f47bb5 · outbound

This paper cites Evoprompting: Language models for code-level neural architecture search.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Evoprompting: Language models for code-level neural architecture search

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.262489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.262489Z digest=sha256:d203980281f3fc8ede9d67e4cd1eb0e03784e6b6ab19c05b5f82515198d513b3

Observation c8e8702e-c973-4773-9c5a-e88d080d5bb2 · outbound

This paper cites Boosting of thoughts: Trial-and-error problem solving with large language models.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Boosting of thoughts: Trial-and-error problem solving with large language models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.265767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.265767Z digest=sha256:69d91617d616f8bd2c28a6b50c8139f247ad777b67ea3fd00353b81bb13e81b8

Observation a81ac4af-20e0-419a-9ab4-5c286fffdfd7 · outbound

This paper cites When is tree search useful for LLM planning? it depends on the discriminator.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks When is tree search useful for LLM planning? it depends on the discriminator

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.269107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.269107Z digest=sha256:bff0e1203f0f88c2c315f32322c6007674aadb74dcc726aa2def19e64df24a9f

Observation 26ce8d78-31de-43f7-a26e-aeb2a8f44417 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Training Verifiers to Solve Math Word Problems

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.272609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.272609Z digest=sha256:dc974aa7f709abd53ddfecb14376441184733f17d0580abbfbd4b62066737a37

Observation 9f58ae40-ccf0-4256-9a5c-ceeb42e48724 · outbound

This paper cites Generating code world models with large language models guided by monte carlo tree search.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Generating code world models with large language models guided by monte carlo tree search

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.276505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.276505Z digest=sha256:a5a8c512b908835f620a64f90286a282a8aaf81ca3a00494f7d3b442f0ffe731

Observation 7ed9e188-510d-4ef6-8915-4a24e18c2c51 · outbound

This paper cites Minedojo: Building open-ended embodied agents with internet-scale knowledge.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Minedojo: Building open-ended embodied agents with internet-scale knowledge

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.280079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.280079Z digest=sha256:97866ea9e7a85c6cd88b169d7342ce3701ec238d58579df4101ac87c2e5af64a

Observation 4a8ea224-44d9-4c42-bbe4-61d127990c06 · outbound

This paper cites Natural Language Reinforcement Learning.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Natural Language Reinforcement Learning

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.283216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.283216Z digest=sha256:1fee01fce596af6d50bebff5f1b1a33379324b224a6571f58d06b340eac8de41

Observation cfab924b-a814-480e-ba2e-9038f5fc3abf · outbound

This paper cites PATHFINDER : Guided search over multi-step reasoning paths.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks PATHFINDER : Guided search over multi-step reasoning paths

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.287013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.287013Z digest=sha256:18e7babc3c1fc4120b102ea4e7c8ebe8db9388333feb46c0d39d55ac7b059146

Observation 3e8ad0c8-8da5-4a21-8d35-f006c1c86ff8 · outbound

This paper cites Leveraging pre-trained large language models to construct and utilize world models for model-based task planning.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Leveraging pre-trained large language models to construct and utilize world models for model-based task planning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.290452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.290452Z digest=sha256:fb0fbd2fa1202619f43155a5ad3ef702750183a89c34f8eede27c792c03e0f03

Observation d766ec42-3441-4df6-80f0-71f3531b0ced · outbound

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

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.294040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.294040Z digest=sha256:d981e15dfdb8426d5d3c9b9315dbc8305f89bdedd7d8d9984963838b6034ec4e

Observation 756355b2-484a-4751-85c7-2e15f652fa1c · outbound

This paper cites Reasoning with language model is planning with world model.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Reasoning with language model is planning with world model

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.297853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.297853Z digest=sha256:743c257c8c11f3c4a8b3ec8c30498804ff77139b21e3b65d2d6237fdb3b741e0

Observation a1647f62-e47d-498a-85fb-5f39dd81f0c3 · outbound

This paper cites Interactive fiction games: A colossal adventure.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Interactive fiction games: A colossal adventure

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.301415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.301415Z digest=sha256:aef2e661e061a03ba92330e373d8b53190046faf53a48445f1a1f28973d09492

Observation 1f41b699-62be-4b38-8a54-7c1d404fa3f8 · outbound

This paper cites Measuring coding challenge competence with APPS.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Measuring coding challenge competence with APPS

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.305204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.305204Z digest=sha256:8361f42b0e86cb69173b0a3365937e73f6b1d5b1fad99dd70402e18df43e7a96

Observation d0530951-ba51-49bc-97c0-bfe83701629b · outbound

This paper cites Measuring mathematical problem solving with the MATH dataset.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Measuring mathematical problem solving with the MATH dataset

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.308662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.308662Z digest=sha256:12ac779cdb42767b644c0ebf84bfdae929e9628b25621139edb1f5c3a021b469

Observation 499e9b2f-94fa-45fb-a609-2ea32b1ab317 · outbound

This paper cites Tree-planner: Efficient close-loop task planning with large language models.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Tree-planner: Efficient close-loop task planning with large language models

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.312319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.312319Z digest=sha256:8bd00bee5f30b1b5b6c276e06770920080ade80ff3cb32e9a094b70ab5902563

Observation ba88d269-8859-4bf3-8e6e-fc05558ceb82 · outbound

This paper cites Understanding the planning of LLM agents: A survey.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Understanding the planning of LLM agents: A survey

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.315734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.315734Z digest=sha256:dd5de8e49d7d3ea2968514fccd220e7fe5d402be632c0199aeac347a4183fa93

Observation 07c5c6b0-e1de-4181-9cd0-a9d98bfda6fd · outbound

This paper cites The consensus game: Language model generation via equilibrium search.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks The consensus game: Language model generation via equilibrium search

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.319703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.319703Z digest=sha256:c18d226029890d53152c5a6c7e7ad0b8acc16a9cb6a38f7504c72b31aaa60e37

Observation ecd1df68-deda-4207-9301-47f17f77ae1d · outbound

This paper cites Language Models (Mostly) Know What They Know.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Language Models (Mostly) Know What They Know

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.323007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.323007Z digest=sha256:aaf97c85a6417738650da33cf75d627cd49a6483d60f673d2f7740e726837fec

Observation 02d454a7-b804-45e1-8310-63d8e486d1d2 · outbound

This paper cites MindStar: Enhancing Math Reasoning in Pre-trained LLMs at Inference Time.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks MindStar: Enhancing Math Reasoning in Pre-trained LLMs at Inference Time

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.326793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.326793Z digest=sha256:2dd8ba545f7792a3e8f55b3dcc6a1f19a03e1a9dc10b985b18ba32a07e7ec02f

Observation 6264904f-635a-4252-b168-470d2b1b9223 · outbound

This paper cites Tree search for language model agents.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Tree search for language model agents

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.330422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.330422Z digest=sha256:95e00ed31018734a9a92e0a791e039f72abb87d376eee2d015a8a315bb58556a

Observation e1813333-5726-40ff-8e7b-d44f434c67f9 · outbound

This paper cites Large language models are zero-shot reasoners.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Large language models are zero-shot reasoners

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.334165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.334165Z digest=sha256:ef0131094310e5c21898b1d641c6ccb5ea064792fe533cca5f19486d140cba44

Observation 689d6942-5653-41e2-9fa4-5ad762a734fa · outbound

This paper cites Pre-trained language models for interactive decision-making.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Pre-trained language models for interactive decision-making

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.743663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.337758Z digest=sha256:6ccd914069d0c656c9f83e094cb67fc5bba31253647efcee426d67c7684510b1

Observation f7a0315a-f39e-436c-959d-fc1077b9f675 · outbound

This paper cites A Review of Prominent Paradigms for LLM-Based Agents: Tool Use (Including RAG), Planning, and Feedback Learning.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks A Review of Prominent Paradigms for LLM-Based Agents: Tool Use (Including RAG), Planning, and Feedback Learning

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.341055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.341055Z digest=sha256:1f344f441f12a97d6055c98194e72fdb036cacf992bb6cf2a28e0a17e7552dd9

Observation cf9b1660-fec3-44c2-a304-e1594423cb85 · outbound

This paper cites Making language models better reasoners with step-aware verifier.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Making language models better reasoners with step-aware verifier

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.344743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.344743Z digest=sha256:aeecda2ca78a9f9ee35b086b7b6bce220c88fc9fd9529cfa54e2487a0b6628d4

Observation 6092914d-e1d6-46b5-89f7-3b4691c06bbe · outbound

This paper cites Strategist: Self-improvement of LLM decision making via bi-level tree search.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Strategist: Self-improvement of LLM decision making via bi-level tree search

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.733643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.348277Z digest=sha256:a76c9e83874a653555bf97b8b52a757905a8f248ce047e7b440b32bf7e7abc4f

Observation b9b20a57-89ae-4ddb-89b4-91a1ac114afe · outbound

This paper cites Let's verify step by step.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Let's verify step by step

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.351629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.351629Z digest=sha256:45595a969d15ed450a62a7da9b0420f6a853040c86814470c6e07394c2124e8d

Observation b1879472-a753-4765-b693-46e389132462 · outbound

This paper cites Teaching models to express their uncertainty in words.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Teaching models to express their uncertainty in words

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.354665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.354665Z digest=sha256:f5a51d09da29a7be4235e5d54abf9cf2663a292d46033a17eafedcc7a59685ec

Observation d3ae6526-b3bc-4272-acc6-47f13aa65ba9 · outbound

This paper cites LLM+P: Empowering Large Language Models with Optimal Planning Proficiency.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks LLM+P: Empowering Large Language Models with Optimal Planning Proficiency

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.357880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.357880Z digest=sha256:6e4802644dae3d97529e1a2dabe087afdd5e2ce25c77564df1d6c5ec9768ec06

Observation 97ee6117-8d60-41f8-bc18-51449382bf88 · outbound

This paper cites Think-on-graph 2.0: Deep and faithful large language model reasoning with knowledge-guided retrieval augmented generation.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Think-on-graph 2.0: Deep and faithful large language model reasoning with knowledge-guided retrieval augmented generation

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.711820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.362414Z digest=sha256:f1a904a41748b9adb5b3230e6321231f3ec47ea9dc468df70e23652f7d2871e2

Observation 96a0dd24-007c-492d-a80a-26e62b173d08 · outbound

This paper cites Self-refine: Iterative refinement with self-feedback.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Self-refine: Iterative refinement with self-feedback

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.700975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.365496Z digest=sha256:11e906fa6514062e0e2cdbbc49f1b6ee83aa15fab9e4f6c8820803cb38d3a94c

Observation 2f89dd90-eae4-48e8-a4b0-af58b05cbeb1 · outbound

This paper cites Self-Refine: Iterative Refinement with Self-Feedback.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Self-Refine: Iterative Refinement with Self-Feedback

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.368745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.368745Z digest=sha256:b281b3ebe26fd9106467e46bb41bd169b101a64ea67182d605efd08fb991a315

Observation 1841f482-5739-460d-a221-032ea43d6e39 · outbound

This paper cites The 1998 ai planning systems competition.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks The 1998 ai planning systems competition

Reference 38

Resolution
verified exact
doi, observed 2026-08-10T19:27:23.650579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.372200Z digest=sha256:dc98fbbe37718262a2c6d8c772128512b52c6d82679ba6a627b685b4e36d32ab

Observation e6127706-98c4-415a-a0f1-ae039598b242 · outbound

This paper cites Llm-a*: Large language model enhanced incremental heuristic search on path planning.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Llm-a*: Large language model enhanced incremental heuristic search on path planning

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.690308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.375804Z digest=sha256:bb8b2234fded65708823e90dd466eea1a3a8ea281be1e5956e1f11fd02e8aa16

Observation e636ad46-0e69-47d6-9841-9354c02f6ee3 · outbound

This paper cites Wang, and Xi Victoria Lin.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Wang, and Xi Victoria Lin

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.678714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.379319Z digest=sha256:f3fb7181aced72d4d953f7ad564d90aeb5dacef938d5acf14c3ddbf547397eff

Observation dc0e7cc2-c3b2-423b-a9de-f6fb207ba462 · outbound

This paper cites Training language models to follow instructions with human feedback.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Training language models to follow instructions with human feedback

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.382670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.382670Z digest=sha256:da0356614c532c9107b46d40432fb46a667ae308725192d684371795cb0095ed

Observation e273d0c2-f7b6-4178-bbcd-dd407fb09138 · outbound

This paper cites Feedback loops with language models drive in-context reward hacking.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Feedback loops with language models drive in-context reward hacking

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.661551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.385870Z digest=sha256:98f4a99a6a251b466dafafadd803595733faaf4dc3406429b637d6433f07c01e

Observation e99a29e7-28af-437e-9e8e-9f8b0ed00996 · outbound

This paper cites Inference-Time Computations for LLM Reasoning and Planning: A Benchmark and Insights.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Inference-Time Computations for LLM Reasoning and Planning: A Benchmark and Insights

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.389453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.389453Z digest=sha256:8e1631bc1864da7919c67ec4a089ae05b8dcf6ea18ab7be97abbf8a9adb74028

Observation f8f2032e-0fbc-479b-9f61-49bb685aca02 · outbound

This paper cites Virtualhome: Simulating household activities via programs.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Virtualhome: Simulating household activities via programs

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.651036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.393213Z digest=sha256:4e4ee2badf41fd242924d35ee9d586602870a886a388f6f7555fd85b3ab2d815

Observation 7cdbaa25-2534-423d-84db-6be5e8c79451 · outbound

This paper cites Agent q: Advanced reasoning and learning for autonomous ai agents.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Agent q: Advanced reasoning and learning for autonomous ai agents

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.639245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.398304Z digest=sha256:ae1e9ea08a293e68e4f5c7c82e5de6422181ee40ed12d16da5cddff171cb9831

Observation b14fb7fc-6761-4b19-9300-58e94a5d3ee7 · outbound

This paper cites Mutual reasoning makes smaller LLM s stronger problem-solver.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Mutual reasoning makes smaller LLM s stronger problem-solver

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.404581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.404581Z digest=sha256:d723afeb4c572397ed1eaf7641ac57272416b142f38a236bd072f9b0f4b9d110

Observation ed3bd655-7a9f-40b6-9a8c-97f56e450b90 · outbound

This paper cites Recursive introspection: Teaching language model agents how to self-improve.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Recursive introspection: Teaching language model agents how to self-improve

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.615783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.408263Z digest=sha256:3e7e96ac10b4f275e477e214a486890a447f03be2b3e7b98c44aa43fdf8d5d69

Observation fd364eea-7f23-40a8-b630-dcae4004c782 · outbound

This paper cites Language models are unsupervised multitask learners.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Language models are unsupervised multitask learners

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.412088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.412088Z digest=sha256:c82950d17a9468e0e103ecfde95e94bdfc376434942ae6f2c9f711fb2a06c29f

Observation 8989981d-6b55-42d3-81fe-b9406b34cedd · outbound

This paper cites Artificial intelligence a modern approach.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Artificial intelligence a modern approach

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.600251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.415810Z digest=sha256:6dd027e3783fe54be8a9f4ce6593374ac80dcbf664a65d33e21701dd29d50758

Observation f820088f-a964-4ad8-bb8c-52d01e5285d7 · outbound

This paper cites Whose Opinions Do Language Models Reflect?.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Whose Opinions Do Language Models Reflect?

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.419341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.419341Z digest=sha256:f66038b19d25cce95164156e6d8acd86fb4b1a22a9c7bedb7706499d7ace09fc

Observation 8840e2d8-d2f0-4ca8-addc-f8f65c5ea3ac · outbound

This paper cites Monte carlo planning with large language model for text-based games.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Monte carlo planning with large language model for text-based games

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.589976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.423396Z digest=sha256:76bc0cca91924299435f0e975a6cf6cd7ba3011019b2fce52c8f22b1df9bda80

Observation 68541345-4d7c-4d15-a702-a890753ee148 · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning, 2023.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Reflexion: Language agents with verbal reinforcement learning, 2023

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.426776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.426776Z digest=sha256:d58ea7c2c8af148f7607f965a5142c56bf95d183704da1a06b27c0e5263b9661

Observation 7f56b684-119b-4bf6-a1e0-af0eaa759452 · outbound

This paper cites \ ALFW \ orld: Aligning text and embodied environments for interactive learning.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks \ ALFW \ orld: Aligning text and embodied environments for interactive learning

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.573039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.430132Z digest=sha256:41a444df49f094e35544babb9aded1e049bf4226821420bfd6fa3fd2b5b33746

Observation 9f4bc174-0db3-40d1-b008-268f4d619590 · outbound

This paper cites Blocks world revisited.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Blocks world revisited

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.433709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.433709Z digest=sha256:814bcef2105c72dcc6890c7c814d26e4614ee2b2c57b9f6c8219e5860f8ca301

Observation a128b41b-b0ee-4ba5-a5fe-1c57f63ed2e8 · outbound

This paper cites Scaling test-time compute optimally can be more effective than scaling LLM parameters.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Scaling test-time compute optimally can be more effective than scaling LLM parameters

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.437305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.437305Z digest=sha256:6b11f53415afc9b24f975469c202d6544d0626a24dfe2a7b73d2426b43b74a4d

Observation 20e1b33d-e2aa-44aa-9bcb-55d7da49e4dd · outbound

This paper cites Informing reinforcement learning agents by grounding natural language to markov decision processes, 2024.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Informing reinforcement learning agents by grounding natural language to markov decision processes, 2024

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.556662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.440663Z digest=sha256:e4335d29e091b947b72057a3134bb420538e14304b96ff1f5c5e795f77d7aacf

Observation ee676fa0-5363-4a68-bdcb-251ef1b83b8d · outbound

This paper cites Think-on-graph: Deep and responsible reasoning of large language model on knowledge graph.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Think-on-graph: Deep and responsible reasoning of large language model on knowledge graph

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.546141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.444354Z digest=sha256:da47a90dfc052ccbfb38ec603c269e6d5188ef8433fbb4de6cfc321c4713f9b6

Observation 22fa9e8f-535a-4fc7-8e7c-ba31db9479fe · outbound

This paper cites Reinforcement learning: An introduction.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Reinforcement learning: An introduction

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.447759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.447759Z digest=sha256:cc87de3b69469c6edd64e5eefa6c5b3464a001d39353557d0d7a36e34f0f7306

Observation a7f5397f-51e8-4e4e-b7fe-85b568251308 · outbound

This paper cites Planbench: An extensible benchmark for evaluating large language models on planning and reasoning about change.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Planbench: An extensible benchmark for evaluating large language models on planning and reasoning about change

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.526763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.451235Z digest=sha256:054bc8934471a92322df16f4bacec3e00ecacd061c52ce204640a2bbbbe99a92

Observation 9c6afc76-19d6-476e-909f-ab1a82aa0871 · outbound

This paper cites On the planning abilities of large language models - a critical investigation.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks On the planning abilities of large language models - a critical investigation

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.513529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.454444Z digest=sha256:99b63a7dc63a1315474693a8780d6869642322a7fcc18ef97b90e1c05da2703f

Observation 3e8cccae-fc11-42ca-9674-325d7bf3135a · outbound

This paper cites Alphazero-like tree-search can guide large language model decoding and training, 2024.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Alphazero-like tree-search can guide large language model decoding and training, 2024

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.499686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.457813Z digest=sha256:14bf5a9b31707e05c9684dbb201c29bc9f2f01881ecdb9c9b0bad353af57bc8e

Observation 548cc433-55ad-44a5-b2a9-256a4618fa2c · outbound

This paper cites Q*: Improving Multi-step Reasoning for LLMs with Deliberative Planning.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Q*: Improving Multi-step Reasoning for LLMs with Deliberative Planning

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.461086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.461086Z digest=sha256:cf4dab607578c789f3d5787e1e0f03057df6a2de59139c6d2c035e1eba1c78df

Observation 7eb567fa-0df3-4673-ad19-5e690bc79311 · outbound

This paper cites Hendryx, Summer Yue, and Hugh Zhang.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Hendryx, Summer Yue, and Hugh Zhang

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.486778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.464955Z digest=sha256:1a88d77175d0da1d2aacfcb8b653a68b6d8900aa73db5573bab7a6188828bd8a

Observation 8fd50480-1a12-4abf-a7da-57b2ff437323 · outbound

This paper cites Efficient evolutionary search over chemical space with large language models.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Efficient evolutionary search over chemical space with large language models

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.476064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.468438Z digest=sha256:ae49f56a3824b76abbf5e0ed08ce5e5f7de1ee79f285f205fa66354dc75b5033

Observation 8f5873dc-3fa2-4cd1-9002-0bf01d792769 · outbound

This paper cites A survey on large language model based autonomous agents.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks A survey on large language model based autonomous agents

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.465901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.471754Z digest=sha256:1903d89af515e76e12121b59ee4fa670536e9dcaa81c37c7677aebea2f09a31b

Observation 21a5fe52-8170-4875-9dea-a756e2f2b961 · outbound

This paper cites Task-completion dialogue policy learning via M onte C arlo tree search with dueling network.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Task-completion dialogue policy learning via M onte C arlo tree search with dueling network

Reference 66

Resolution
verified exact
doi, observed 2026-08-10T19:27:23.633808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.474595Z digest=sha256:afca4934a5267242465b5ddb335d4a2e1f48e7f9744afb9e71b78c7790e287d1

Observation 8df0f6e2-4459-43de-9e53-ec8d6cea2e76 · outbound

This paper cites From lsat: The progress and challenges of complex reasoning.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks From lsat: The progress and challenges of complex reasoning

Reference 67

Resolution
metadata mismatch
raw_fallback, observed 2026-08-10T19:27:23.873464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.477801Z digest=sha256:cf66f714788bf8ada24bd808ea8c51e664ffb631e7fb4a1f8fc8b59fd5f425e4

Observation 8b4a260f-c9f5-4391-867c-fbe805d86b41 · outbound

This paper cites Persuasion for good: Towards a personalized persuasive dialogue system for social good.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Persuasion for good: Towards a personalized persuasive dialogue system for social good

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.480844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.480844Z digest=sha256:d8801b89c85a30e30e727beca8e632edfe4a8eb823c21736468c1ca2e05001f3

Observation 99f573bc-3a73-4acb-b6fc-610ce9bd5bfc · outbound

This paper cites Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.483793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.483793Z digest=sha256:8ceb6e4a19f50c32c4a9437ad94a7fa326982472790a252b8fab6b2a2f063408

Observation 05dd5b64-0abc-495d-824f-3772e119a245 · outbound

This paper cites Learning from delayed rewards.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Learning from delayed rewards

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.486638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.486638Z digest=sha256:87388197390c9f0be0ec6a19d8438eabe056eb57e98eebac47f7bd7f3d35855c

Observation 0d609aa8-6e50-43e3-8e8c-e4b31598e0cd · outbound

This paper cites Chi, Quoc V Le, and Denny Zhou.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Chi, Quoc V Le, and Denny Zhou

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.489566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.489566Z digest=sha256:93255a6fcc57258989687c265f599df3d22cbd2fe96d06aaa5d76b8b51ae38f3

Observation 97e1ecc8-5b49-4f46-b17a-071a1e3607d4 · outbound

This paper cites Self-evaluation guided beam search for reasoning.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Self-evaluation guided beam search for reasoning

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.433124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.492601Z digest=sha256:2e9fa4b563578fa380bdf4e86f07e748fc21616ea2fa0240612c0e84302a71e7

Observation 762e91d1-ed07-44cc-8f27-572fac1edd02 · outbound

This paper cites On the Tool Manipulation Capability of Open-source Large Language Models.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks On the Tool Manipulation Capability of Open-source Large Language Models

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.495454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.495454Z digest=sha256:e253c5e98e6036577d0ef9b78a1ddac8f471f755122c208040d0d42ce72ad8f9

Observation 94292469-b5cd-4256-aebd-b0b83979f114 · outbound

This paper cites an unresolved cited work.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Unresolved cited work

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.498691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.498691Z digest=sha256:7c2b7c90970ef84b41e0711b6014c85a2bba63e7d34b2bc43aafeae5bdd7f2e3

Observation 0c1bcde0-415f-47b3-a589-c2117be0ae93 · outbound

This paper cites Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.501890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.501890Z digest=sha256:565ebcc9db737fa9d851670ad7eeffb5d9f7bcfff6897d02b4095da309a7fd4c

Observation 6106a7e5-2d14-4441-87e1-a412c293bf00 · outbound

This paper cites De FT : Decoding with flash tree-attention for efficient tree-structured LLM inference.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks De FT : Decoding with flash tree-attention for efficient tree-structured LLM inference

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.421652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.504876Z digest=sha256:ec05051fdefee9c9dd645ae64270c7ca4eaa2b3d06659a376078b85dffd00c3c

Observation 841c5590-209c-4e63-9104-db7dbc716795 · outbound

This paper cites Webshop: Towards scalable real-world web interaction with grounded language agents.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Webshop: Towards scalable real-world web interaction with grounded language agents

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.508179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.508179Z digest=sha256:9332716b245f4c092ef07fba3f746e03f0e99f81c7b86c7e7904d71e72464dff

Observation d9ef6a6c-bec9-49e9-b445-17fd20fa6ef7 · outbound

This paper cites Griffiths, Yuan Cao, and Karthik Narasimhan.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Griffiths, Yuan Cao, and Karthik Narasimhan

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.510905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.510905Z digest=sha256:1711da60778ac038ab0d4f13131a29f60a5ac51aefd4395e784b26486c146fe9

Observation 96d2f1cd-1970-49fd-873b-4ca1067aa208 · outbound

This paper cites React: Synergizing reasoning and acting in language models.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks React: Synergizing reasoning and acting in language models

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.513716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.513716Z digest=sha256:4c33bb21073ac2484f41b0c27fbcb25b563f36d71e50cf7fe6826d5c500ed877

Observation a7f26d23-066d-4b20-bb90-4ebb26899679 · outbound

This paper cites The value of semantic parse labeling for knowledge base question answering.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks The value of semantic parse labeling for knowledge base question answering

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.517047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.517047Z digest=sha256:cb9297b1fd20f427289c19195992fe35ef8f912aa4dbb3844f6b3dd7cfc508f5

Observation b6b50276-5f1c-4326-8e98-d1ccd6ac9584 · outbound

This paper cites Prompt-based monte-carlo tree search for goal-oriented dialogue policy planning.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Prompt-based monte-carlo tree search for goal-oriented dialogue policy planning

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.391256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.520789Z digest=sha256:a4bc11f2ad4829e2fe3fb34aa2efba207fe4e80b85f8023e8e9114c4b7f6cdf4

Observation 1d69ce47-b12b-4395-af27-6010f0eb501d · outbound

This paper cites DOTS : Learning to reason dynamically in LLM s via optimal reasoning trajectories search.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks DOTS : Learning to reason dynamically in LLM s via optimal reasoning trajectories search

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.381224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.524360Z digest=sha256:fcfd84d5f485296ca9a3c63a86ef0b195e4e0cb0144361192ef16c592f73bea5

Observation 9a0f076a-f2c2-4984-8f57-e9ad4f3e5e97 · outbound

This paper cites Re ST - MCTS *: LLM self-training via process reward guided tree search.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Re ST - MCTS *: LLM self-training via process reward guided tree search

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.528057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.528057Z digest=sha256:6204b3923b95e1e98d35982dae5d1b1fd5acca0ff32a8990e5841098245a5a30

Observation ca10d0da-a330-4e5c-ab2f-b4b2debb5720 · outbound

This paper cites AF low: Automating agentic workflow generation.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks AF low: Automating agentic workflow generation

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.363686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.531519Z digest=sha256:5030b9792c4c165bfc2ab75760f8d61910493d8e31930f93c1a4e18609d5104e

Observation bb449357-6d1f-49bc-ae20-74fac4be7a20 · outbound

This paper cites Tenenbaum, and Chuang Gan.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Tenenbaum, and Chuang Gan

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.352603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.534829Z digest=sha256:abc143a311cdff87dbb0b908d9104823a1274052ef7a7f39b774faf70914bb38

Observation 1df432bb-c701-48c4-98fe-c74a16db7b0e · outbound

This paper cites Chain of preference optimization: Improving chain-of-thought reasoning in LLM s.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Chain of preference optimization: Improving chain-of-thought reasoning in LLM s

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.340168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.538247Z digest=sha256:71cd9f6dea147a548a7f0c716389b6c55954a2c610669831efc1cfe065e4df2c

Observation 2f4bb1ff-60e3-41e3-a9bf-9d2f5f1852be · outbound

This paper cites Large language models as commonsense knowledge for large-scale task planning.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Large language models as commonsense knowledge for large-scale task planning

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.328196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.541604Z digest=sha256:0c271172a3816841ded56ae5f191270c0bca07cf30c5cca904a40b155191c097

Observation 0aaba617-d686-4206-8946-3d4258962de0 · outbound

This paper cites What makes large language models reason in (multi-turn) code generation? In The Thirteenth International Conference on Learning Representations, 2025.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks What makes large language models reason in (multi-turn) code generation? In The Thirteenth International Conference on Learning Representations, 2025

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.316942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.544939Z digest=sha256:93781ace9a694335366077962d56c5290cc8e88e3eb85c373e5b7d9ccdaf1515

Observation 2856245f-d954-46c3-92ba-99b3608fbd86 · outbound

This paper cites Analytical reasoning of text.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Analytical reasoning of text

Reference 89

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.548246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.548246Z digest=sha256:eb1a92e8a85dbc5762e96fe706cb99b1de6659feaa6fb83f1862674456312457

Observation 7431a7ec-604a-4bc7-bd47-a25fc223e0b3 · outbound

This paper cites AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.551756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.551756Z digest=sha256:de3c353ad7506af1258e20303998f77d3a71d52fd6ad3e5ebe804181673be90e

Observation 19c295eb-5ebf-43f8-94eb-bd995e182ab2 · outbound

This paper cites Language agent tree search unifies reasoning acting and planning in language models, 2024 a.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Language agent tree search unifies reasoning acting and planning in language models, 2024 a

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.305525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.555678Z digest=sha256:ede33d089f4ba39c77977d87bef41d828a03a312f6cfbef1a9dd2810a5991722

Observation 4e11743c-2ebd-4eeb-bce6-44a7b7a2d5fc · outbound

This paper cites an unresolved cited work.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Unresolved cited work

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.559182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.559182Z digest=sha256:1520637de6bc3b91c99441b5be6fc6ca7d5ad795c9dbbb59bc2d7f7d4f9c701e

Observation b338bda1-304c-4e18-b4dc-3548bdaa6c14 · outbound

This paper cites Xu, Hao Zhu, Xuhui Zhou, Robert Lo, Abishek Sridhar, Xianyi Cheng, Tianyue Ou, Yonatan Bisk, Daniel Fried, Uri Alon, and Graham Neubig.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Xu, Hao Zhu, Xuhui Zhou, Robert Lo, Abishek Sridhar, Xianyi Cheng, Tianyue Ou, Yonatan Bisk, Daniel Fried, Uri Alon, and Graham Neubig

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.287046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.562544Z digest=sha256:c7cfed36e7735c420f3db539ec5f8232de29761c8e405895e202b49436f7e1f7

Observation adf9ccfd-5e11-48d3-82dc-7cee0e1bf652 · outbound

This paper cites Rossi, Somdeb Sarkhel, and Chao Zhang.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Rossi, Somdeb Sarkhel, and Chao Zhang

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:27:24.276737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-10T19:27:23.565972Z digest=sha256:b51cd8f5252b0199bc385e2832c8fe583dfc06e9b9cfa46124a7b23503de9260

Observation 5115e76c-f7f0-4c2e-8baa-f21ee7e9ae02 · outbound

This paper cites write newline.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks write newline

Reference 95

Resolution
unresolved
no resolver link, observed 2026-08-10T19:27:23.569311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T19:27:23.569311Z digest=sha256:87fdf33ce1412c647e35ef8c0f1572e88ad8da82b37dd6a41f1abb9aa81b74a2

Pith citing papers

Observation de7ee1c1-9ed3-4adb-86e6-a016d3d0146e · inbound

On Almost Surely Safe Alignment of Large Language Models at Inference-Time cites this paper.

On Almost Surely Safe Alignment of Large Language Models at Inference-Time A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-09T16:18:40.793196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:18:40.793196Z digest=sha256:2b6c6ac3b59bea89d0355d8749a447d4d3c77e21243ac3d8dbcbb6a950a0cd50

Observation 27e8b020-eb5b-4619-9341-d453c3383f62 · inbound

Deciphering Trajectory-Aided LLM Reasoning: An Optimization Perspective cites this paper.

Deciphering Trajectory-Aided LLM Reasoning: An Optimization Perspective A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T14:13:07.442289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:13:07.442289Z digest=sha256:1c055933c6d91537ed46b29950dcd96b8c7a990a2f0f6f447aa360c47625597d

Observation 4a9f9166-e000-46ce-b89f-e663b8216b5e · 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 A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:28.325869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:35:28.325869Z digest=sha256:414ef33d9c18dce9697dbc39879903c7168810f68f9c260d647765b4bb5bf960

Observation 44649f0b-322d-4931-b163-64818cd5a2a0 · inbound

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning cites this paper.

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks

Reference 106

Resolution
verified exact
arxiv_id, observed 2026-07-04T08:09:40.661608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-26T12:15:08.304150Z digest=sha256:85bcc5f013cf78cd2437559c7bad8812c275e7311737cf9f381006f024ec4198