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Paper Citation Record · LEDGER

Enhancing Test-Time Scaling of Large Language Models with Hierarchical Retrieval-Augmented MCTS

As of 10 August 2026, this Paper Citation Record lists 10 of 10 outbound references and 2 inbound Pith citation observations for arXiv:2507.05557.

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

pith.paper-citation-record.v1
2507.05557 v1

Coverage vector

measured 10 of 10 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:28:12.738961Z

measured 12 of 12 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-09T00:45:00.847714Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T00:45:49.112586Z

Reference resolution

10 of 10 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5211907d-06e4-426e-8935-9284acb209e6 · outbound

This paper cites CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing.

Enhancing Test-Time Scaling of Large Language Models with Hierarchical Retrieval-Augmented MCTS CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T19:28:12.230373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:28:12.230373Z digest=sha256:2d13340538d6e9960e6b6c844403c9e1660eae98abf817388826221739b1f802

Observation 268a011c-3fc7-4cde-9361-b86dd0bb066e · outbound

This paper cites Let's Verify Step by Step.

Enhancing Test-Time Scaling of Large Language Models with Hierarchical Retrieval-Augmented MCTS Let's Verify Step by Step

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T19:28:12.405488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:28:12.405488Z digest=sha256:fe911cbd65cd3177a2f3d489a13de68c98e6744dd739914c9d4f923d768b7110

Observation fdc52470-24ca-4de1-b926-102f689a3f5a · outbound

This paper cites PhyX: Does Your Model Have the "Wits" for Physical Reasoning?.

Enhancing Test-Time Scaling of Large Language Models with Hierarchical Retrieval-Augmented MCTS PhyX: Does Your Model Have the "Wits" for Physical Reasoning?

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T19:28:12.530736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:28:12.530736Z digest=sha256:1c02774b07e836d8599b75332ac3b64849ebb0cabe5854be0f50bd413701b172

Observation 728d02f4-1b28-4828-9f8e-82aee73fa4b0 · outbound

This paper cites ParallelComp: Parallel Long-Context Compressor for Length Extrapolation.

Enhancing Test-Time Scaling of Large Language Models with Hierarchical Retrieval-Augmented MCTS ParallelComp: Parallel Long-Context Compressor for Length Extrapolation

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T19:28:12.592615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:28:12.592615Z digest=sha256:693d6801e7fbd473f2487512508d72dd9b62bf23ee8e1856eba519cb6d62442f

Observation 65ab9e98-8f2c-4a06-a64b-953bfd1078f7 · outbound

This paper cites Ling Yang, Zhaochen Yu, Tianjun Zhang, Shiyi Cao, Minkai Xu, Wentao Zhang, Joseph E Gonzalez, and Bin Cui.

Enhancing Test-Time Scaling of Large Language Models with Hierarchical Retrieval-Augmented MCTS Ling Yang, Zhaochen Yu, Tianjun Zhang, Shiyi Cao, Minkai Xu, Wentao Zhang, Joseph E Gonzalez, and Bin Cui

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T19:28:12.674907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:28:12.674907Z digest=sha256:703a85d25545424c72b04c2bb5b3c3f8d0ab9867b189383b06490487bba128a2

Observation a1a66aae-31d1-48b2-8258-6f5906fe83b4 · outbound

This paper cites Advances in neural information processing systems, 36:11809–11822.

Enhancing Test-Time Scaling of Large Language Models with Hierarchical Retrieval-Augmented MCTS Advances in neural information processing systems, 36:11809–11822

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T19:28:12.738961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:28:12.738961Z digest=sha256:20b827061d5c1657139916f3baca168f63f811a88c0edf9d39cdebf09215761e

Observation 380ebdd7-ddef-48ae-b218-d146456d33c1 · outbound

This paper cites MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms.

Enhancing Test-Time Scaling of Large Language Models with Hierarchical Retrieval-Augmented MCTS MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-06T19:28:12.063407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:28:12.063407Z digest=sha256:2d994f018b9906b323823b6bc3caf38a49d0b662f9beb4b06105122a7a57ecc4

Observation e1d90dd1-c705-42d0-baef-f00aca515744 · outbound

This paper cites Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training.

Enhancing Test-Time Scaling of Large Language Models with Hierarchical Retrieval-Augmented MCTS Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T19:28:12.161024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:28:12.161024Z digest=sha256:43d195110ed4319ea8f4cd9c51eccf86e1ca3a72a69c979d7cab596935e46ba2

Observation 319fb461-4b2f-4902-9b73-c49380a7754e · outbound

This paper cites Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning.

Enhancing Test-Time Scaling of Large Language Models with Hierarchical Retrieval-Augmented MCTS Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T19:28:12.438888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:28:12.438888Z digest=sha256:60e2809f598cb1b4924d214f8187cf42866c8f7962e2c0980f6658a965da775e

Observation 6c2624e4-c766-48db-adb9-7fdc2332769a · outbound

This paper cites rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking.

Enhancing Test-Time Scaling of Large Language Models with Hierarchical Retrieval-Augmented MCTS rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-06T19:28:12.313777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:28:12.313777Z digest=sha256:486ed9dc8e0aaf98a4d7d8bcd2101d62d00877ad01daebf616688980601b18c8

Pith citing papers

Observation 2408d9a4-ecd8-4a7e-9c7c-ff94672e3e9e · inbound

Mathematical Reasoning via Intervention-Based Time-Series Causal Discovery Using LLMs as Concept Mastery Simulators cites this paper.

Mathematical Reasoning via Intervention-Based Time-Series Causal Discovery Using LLMs as Concept Mastery Simulators Enhancing Test-Time Scaling of Large Language Models with Hierarchical Retrieval-Augmented MCTS

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-11T03:55:57.641565Z

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=2026-05-11T02:05:48.483640Z digest=sha256:3050b0e99641228a5ad5b8d4cf534a8e7a079ec4ce2c3d3cc176a6ba48a74325

Observation b2e40311-3359-473b-91cc-597d7112a023 · inbound

MILES: Modular Instruction Memory with Learnable Selection for Self-Improving LLM Reasoning cites this paper.

MILES: Modular Instruction Memory with Learnable Selection for Self-Improving LLM Reasoning Enhancing Test-Time Scaling of Large Language Models with Hierarchical Retrieval-Augmented MCTS

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-07-09T00:45:49.113840Z

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=2026-07-09T00:45:00.847714Z digest=sha256:381729e788a05854b2af0fcbabb5360c0d9f90608e0881e633428379c33b795c