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Paper Citation Record · LEDGER

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs

As of 14 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2509.06284.

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

pith.paper-citation-record.v1
2509.06284 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T23:56:34.906593Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b111c604-729e-4ff4-9dd0-5f11abf9d25f · outbound

This paper cites InProceedings of the 2024 Con- ference on Empirical Methods in Natural Language Processing, pages 1107–1128.

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs InProceedings of the 2024 Con- ference on Empirical Methods in Natural Language Processing, pages 1107–1128

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:56:35.134176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-04T23:56:34.878238Z digest=sha256:fe9e8f30def9056e527bd52fba668b66a724eb102cb3fc031aced38fc9487b8f

Observation c0d745b1-6358-4e6c-bdab-9dfe732ff9e9 · outbound

This paper cites InProceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 8154–8173.

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs InProceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 8154–8173

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:56:35.125503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-04T23:56:34.881113Z digest=sha256:fdc29b57d7cab2551e57a56e525cb12b87cedb3b777fc68126d1ca51ee182722

Observation 30564805-3eb1-4c07-9a99-5995ef44e848 · outbound

This paper cites MathPrompter: Mathematical Reasoning using Large Language Models.

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs MathPrompter: Mathematical Reasoning using Large Language Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-04T23:56:34.886866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:56:34.886866Z digest=sha256:5f03abc812f822dd87d4255955b8d13a601735bc8b0c9f1a4a8b77893fca224a

Observation 532a7a83-8582-48f3-abb6-eae8bd688b7c · outbound

This paper cites Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning.

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-04T23:56:34.889878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:56:34.889878Z digest=sha256:06e0ba3e72233ed854bf34070377beeaa634c9a18a7cc04ea1a642df31a9821f

Observation 0a688287-8e14-4c9f-a039-2a47a959cfb3 · outbound

This paper cites BEATS: Optimizing LLM Mathematical Capabilities with BackVerify and Adaptive Disambiguate based Efficient Tree Search.

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs BEATS: Optimizing LLM Mathematical Capabilities with BackVerify and Adaptive Disambiguate based Efficient Tree Search

Reference 10

Resolution
metadata mismatch
local_arxiv, observed 2026-08-04T23:56:34.984037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-04T23:56:34.892863Z digest=sha256:94f3bf97230bb5ead67e33eb4d51493a2d881ef5d56647031190ca2fb7c501a4

Observation 129635e6-fa89-48c8-9997-8fa4768e56a6 · outbound

This paper cites From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation.

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-04T23:56:34.895604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:56:34.895604Z digest=sha256:2c9b4535c620c05d1eb2bcbfb1564b704fc23fedc85e1c8064cdd4a1dbb12380

Observation 7906da50-64bc-435f-aac0-c75e13b24a33 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-04T23:56:34.898309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:56:34.898309Z digest=sha256:8956f7c5b3c9c3c4017eb38d56d43cfc88a037e272c784fd7dc7b56303c76c2e

Observation ce807850-8492-43ab-afc0-b59d4c399509 · outbound

This paper cites Beyond Examples: High-level Automated Reasoning Paradigm in In-Context Learning via MCTS.

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs Beyond Examples: High-level Automated Reasoning Paradigm in In-Context Learning via MCTS

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-04T23:56:34.901101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:56:34.901101Z digest=sha256:037973ba857272716f3139285c2fc1e2ad50b856b732681ddf435c91d9e55946

Observation dcd1332c-298e-4032-89b0-f7deb58b1d2a · outbound

This paper cites BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning.

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning

Reference 14

Resolution
metadata mismatch
local_arxiv, observed 2026-08-04T23:56:34.946482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-04T23:56:34.903930Z digest=sha256:4184cad76c055892333c705b023cddc30d500da7bfa0314e59bb5cbee3194f9d

Observation 459d6664-00cf-4043-9d8f-31c42da7bb3c · outbound

This paper cites A Survey of Large Language Models.

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs A Survey of Large Language Models

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-04T23:56:34.906593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:56:34.906593Z digest=sha256:4bfe0a16afcfaaf3d51e0645aa0f2a25ca48d0bec7cd201ca56ec925eb1aba60

Observation 1426a38b-5805-48e8-8a7f-9129cf307d1e · outbound

This paper cites Guillaume Chaslot, Sander Bakkes, Istvan Szita, and Pieter Spronck.

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs Guillaume Chaslot, Sander Bakkes, Istvan Szita, and Pieter Spronck

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T23:56:35.142334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-04T23:56:34.872394Z digest=sha256:9bb76cb9e6a08ffcc621918b14553ba9eb333c4b0f2c605e5eb3144cce975adb

Observation 9be4d75d-9551-4c0d-b79e-868da5160091 · outbound

This paper cites Towards Reasoning in Large Language Models: A Survey.

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs Towards Reasoning in Large Language Models: A Survey

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-04T23:56:34.883946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:56:34.883946Z digest=sha256:4585791fd162900255cee89a90a5126fd478de6eb72c89b5cc9205842173bccf

Observation 7f2f6d73-eb90-4b7c-bb21-7c1c20db2760 · outbound

This paper cites GPT-4 Technical Report.

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs GPT-4 Technical Report

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-04T23:56:34.865810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:56:34.865810Z digest=sha256:35d8a9556b346bcfffdccce0e95e8a02b30210614e6e03b1a5c877652c51fc51

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

This paper cites Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:56:34.869231Z digest=sha256:c0ad91fb78a35749ea54992868b561f2984085e30a613541a9365fe185c784cb

Observation 8bb9ed74-bbe4-4dea-9df4-8ca06909392c · outbound

This paper cites arXiv preprint arXiv:2506.09080.

From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs arXiv preprint arXiv:2506.09080

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-04T23:56:34.875313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:56:34.875313Z digest=sha256:9635e81635473b7164a5fce239004cc1c4b5ce0a0ce419525870998f5523c056

Pith citing papers

No inbound Pith citation observations are available.