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Paper Citation Record · LEDGER

Enhancing Reasoning through Process Supervision with Monte Carlo Tree Search

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2501.01478.

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

pith.paper-citation-record.v1
2501.01478 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T16:18:40.777676Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T04:07:30.508001Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation d70528af-733a-4c3f-b41a-9aa4121e462b · inbound

Efficient Multi-Agent System Training with Data Influence-Oriented Tree Search cites this paper.

Efficient Multi-Agent System Training with Data Influence-Oriented Tree Search Enhancing Reasoning through Process Supervision with Monte Carlo Tree Search

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-23T04:07:30.515018Z

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=2026-05-23T04:06:23.521344Z digest=sha256:115e4d293bdd890c3a52375bfb8bbaca99fd71d2cb3f166c57e42c59f7366f8e

Observation ac704221-d03e-4dad-b832-cde745c3475e · 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 Enhancing Reasoning through Process Supervision with Monte Carlo Tree Search

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-09T16:18:40.777676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:18:40.777676Z digest=sha256:8a1063e32e0146565bac25c8cbace1cad13ef3570787973be5b504fd4a411544

Observation f2319ab1-9b02-4644-be05-7f3e4858c433 · inbound

OctoTools: An Agentic Framework with Extensible Tools for Complex Reasoning cites this paper.

OctoTools: An Agentic Framework with Extensible Tools for Complex Reasoning Enhancing Reasoning through Process Supervision with Monte Carlo Tree Search

Reference 44

Resolution
metadata mismatch
arxiv_id, observed 2026-05-23T02:42:26.364016Z

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=2026-05-23T02:39:18.259822Z digest=sha256:da60e3993e80919f1bf0df311691b72a028604829c2b2716ba972a880744a703

Observation 218116cf-c61e-4fb7-a4af-d3ffff13e233 · inbound

Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains cites this paper.

Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains Enhancing Reasoning through Process Supervision with Monte Carlo Tree Search

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-13T06:07:56.795252Z

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=2026-05-13T06:07:56.678339Z digest=sha256:89f73d02717d1cbf96074641d07a4d4471411bbd00c53b75e82c8a60bbff3954

Observation 6a4c5a46-318a-46b7-b102-08b4c8236c83 · inbound

TaoSR-AGRL: Adaptive Guided Reinforcement Learning Framework for E-commerce Search Relevance cites this paper.

TaoSR-AGRL: Adaptive Guided Reinforcement Learning Framework for E-commerce Search Relevance Enhancing Reasoning through Process Supervision with Monte Carlo Tree Search

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-04T10:53:08.542610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:53:08.542610Z digest=sha256:b6844724f3c12ad5dad8a3658853e02d2b823fda317a441f0a9faaf33eccc316

Observation 4d112cfe-7240-4bba-8276-a021b17a72c6 · inbound

Efficient Reasoning on the Edge cites this paper.

Efficient Reasoning on the Edge Enhancing Reasoning through Process Supervision with Monte Carlo Tree Search

Reference 73

Resolution
unresolved
no resolver link, observed 2026-07-13T23:28:12.790404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T23:28:12.790404Z digest=sha256:f2b05abba5bce88c4c6d54b1ab376194a43d48433b682023af92a165ae21839e

Observation 1a44368c-2632-4ea3-9ac4-f0f4bd86b74e · inbound

Measure Twice, Click Once: Co-evolving Proposer and Visual Critic via Reinforcement Learning for GUI Grounding cites this paper.

Measure Twice, Click Once: Co-evolving Proposer and Visual Critic via Reinforcement Learning for GUI Grounding Enhancing Reasoning through Process Supervision with Monte Carlo Tree Search

Reference 37

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T14:16:06.245387Z

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=2026-05-09T23:05:05.251150Z digest=sha256:99afeade469b29c36e69254180d6a33660f9e14244676277e8a94c73bd9ec72f

Observation 082160ae-529d-4a88-befb-decc08150de8 · inbound

Process Supervision of Confidence Margin for Calibrated LLM Reasoning cites this paper.

Process Supervision of Confidence Margin for Calibrated LLM Reasoning Enhancing Reasoning through Process Supervision with Monte Carlo Tree Search

Reference 41

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T20:41:12.130965Z

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=2026-05-08T08:19:09.437464Z digest=sha256:14d5d402409db9a411648a2e85913f190e50a1ecc958c1720d934535544d3a4d