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Paper Citation Record · LEDGER

Refining Answer Distributions for Improved Large Language Model Reasoning

As of 14 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2412.13292.

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

pith.paper-citation-record.v1
2412.13292 v2

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:20:59.620313Z

measured 27 of 27 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

27 of 27 outbound references displayed

  • verified exact0
  • verified fuzzy6
  • unresolved21
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 26499ff9-785a-4d3a-acb5-8c46eb186d7c · outbound

This paper cites Graph of Thoughts: Solving Elaborate Problems with Large Language Models.

Refining Answer Distributions for Improved Large Language Model Reasoning Graph of Thoughts: Solving Elaborate Problems with Large Language Models

Reference 2

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Unavailable: canonical work link unavailable.

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Observation d2841a24-983a-4f2a-9475-7e3b1105b477 · outbound

This paper cites Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future.

Refining Answer Distributions for Improved Large Language Model Reasoning Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future

Reference 4

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Observation 80adb5e4-1072-4a87-a657-62feaa36f14b · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Refining Answer Distributions for Improved Large Language Model Reasoning Training Verifiers to Solve Math Word Problems

Reference 5

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Observation 603666a3-ed1e-4ff9-9181-601bdb0f911b · outbound

This paper cites an unresolved cited work.

Refining Answer Distributions for Improved Large Language Model Reasoning Unresolved cited work

Reference 6

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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.

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Observation 51b60cdc-43d5-4f05-a7ac-d6c5f522cee2 · outbound

This paper cites Hint-before-Solving Prompting: Guiding LLMs to Effectively Utilize Encoded Knowledge.

Refining Answer Distributions for Improved Large Language Model Reasoning Hint-before-Solving Prompting: Guiding LLMs to Effectively Utilize Encoded Knowledge

Reference 7

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Observation e63615c3-663f-410a-8ab0-267dd4c2f3ba · outbound

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

Refining Answer Distributions for Improved Large Language Model Reasoning CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing

Reference 8

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Observation f17c06e4-e3ca-42c3-96ee-ece2619ae96d · outbound

This paper cites The Llama 3 Herd of Models.

Refining Answer Distributions for Improved Large Language Model Reasoning The Llama 3 Herd of Models

Reference 9

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Observation 95f36640-66b7-4943-834a-008364c83ad9 · outbound

This paper cites GPT-4 Technical Report.

Refining Answer Distributions for Improved Large Language Model Reasoning GPT-4 Technical Report

Reference 11

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Observation 42649661-0a10-473c-9864-6c3b581eb629 · outbound

This paper cites REFINER: Reasoning Feedback on Intermediate Representations.

Refining Answer Distributions for Improved Large Language Model Reasoning REFINER: Reasoning Feedback on Intermediate Representations

Reference 12

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Observation 9b3039ed-0a9d-488b-9b13-3e6012c09c2d · outbound

This paper cites Srivastava, A.

Refining Answer Distributions for Improved Large Language Model Reasoning Srivastava, A

Reference 14

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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.

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Observation af516c37-022e-4df5-ab92-02b73f0a1bfb · outbound

This paper cites LLMs cannot find reasoning errors, but can correct them given the error location.

Refining Answer Distributions for Improved Large Language Model Reasoning LLMs cannot find reasoning errors, but can correct them given the error location

Reference 15

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Observation 2a975cc3-a174-430c-a545-ee37b92dd798 · outbound

This paper cites Emergent Abilities of Large Language Models.

Refining Answer Distributions for Improved Large Language Model Reasoning Emergent Abilities of Large Language Models

Reference 16

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Observation 529ee426-b75b-4e80-8f9c-e7a2fa29eda2 · outbound

This paper cites Tree of Thoughts: Deliberate Problem Solving with Large Language Models.

Refining Answer Distributions for Improved Large Language Model Reasoning Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Reference 17

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Observation 4b153e26-3749-4212-8f15-760e5d54fba9 · outbound

This paper cites Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization.

Refining Answer Distributions for Improved Large Language Model Reasoning Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization

Reference 18

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Observation a5e19c7b-f84e-4546-b05f-ac73e8b3a0b5 · outbound

This paper cites STaR: Bootstrapping Reasoning With Reasoning.

Refining Answer Distributions for Improved Large Language Model Reasoning STaR: Bootstrapping Reasoning With Reasoning

Reference 19

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Observation 4bc161a8-cfbf-420c-9d00-add52fcf8cc3 · outbound

This paper cites Date Understanding.

Refining Answer Distributions for Improved Large Language Model Reasoning Date Understanding

Reference 22

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

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Observation 5cbefa19-4c80-4dc3-9c83-42883f3e51b5 · outbound

This paper cites In order to reduce the API cost of the experiments, we restrict running the more expensive 70B model to only the three most difficult benchmarks.

Refining Answer Distributions for Improved Large Language Model Reasoning In order to reduce the API cost of the experiments, we restrict running the more expensive 70B model to only the three most difficult benchmarks

Reference 23

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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.

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Observation a3a3a763-c9ab-4fb6-b7fa-58267861347a · outbound

This paper cites an unresolved cited work.

Refining Answer Distributions for Improved Large Language Model Reasoning Unresolved cited work

Reference 24

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

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Observation 113404d6-4271-43ef-8f9a-051b23f30785 · outbound

This paper cites The base examples are taken from Zheng et al.

Refining Answer Distributions for Improved Large Language Model Reasoning The base examples are taken from Zheng et al

Reference 26

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

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Observation 1a5710d7-4a35-4ff6-aed7-79f7880e9655 · outbound

This paper cites For Christmas, he got two toys each from his mom and dad.

Refining Answer Distributions for Improved Large Language Model Reasoning For Christmas, he got two toys each from his mom and dad

Reference 27

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

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Observation 14828895-3c49-459b-a03e-4ff8f9d8e925 · outbound

This paper cites Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought.

Refining Answer Distributions for Improved Large Language Model Reasoning Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought

Reference 2015

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Observation 6ec0730a-7343-4440-921f-934de8622b1c · outbound

This paper cites Although these arithmetic problems in the previous benchmarks are relatively simple for humans, LLMs often struggle in solving these types of problems (Patel et al., 2021).

Refining Answer Distributions for Improved Large Language Model Reasoning Although these arithmetic problems in the previous benchmarks are relatively simple for humans, LLMs often struggle in solving these types of problems (Patel et al., 2021)

Reference 2017

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

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Observation 78de401d-ac1a-4a46-8690-5c8e456f2864 · outbound

This paper cites ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs.

Refining Answer Distributions for Improved Large Language Model Reasoning ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs

Reference 2020

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Observation 5b9a5be5-565a-4aad-a329-946b2dda3428 · outbound

This paper cites Improving Factuality and Reasoning in Language Models through Multiagent Debate.

Refining Answer Distributions for Improved Large Language Model Reasoning Improving Factuality and Reasoning in Language Models through Multiagent Debate

Reference 2021

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Observation 8d0ef82c-876b-48ee-8b3a-aa0550c3589b · outbound

This paper cites Self-Convinced Prompting: Few-Shot Question Answering with Repeated Introspection.

Refining Answer Distributions for Improved Large Language Model Reasoning Self-Convinced Prompting: Few-Shot Question Answering with Repeated Introspection

Reference 2022

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source=pdf_text observed=2026-08-11T13:20:59.601734Z digest=sha256:08c848ee30332cf072aa23d858d69ae7831d87cda82af45078f4a50de1f415db

Observation fb22d84d-125e-49fe-a389-7002506c671a · outbound

This paper cites RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model Outputs.

Refining Answer Distributions for Improved Large Language Model Reasoning RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model Outputs

Reference 2023

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source=pdf_text observed=2026-08-11T13:20:59.543487Z digest=sha256:d95648cced96538ec3f49b7ac49f00036cc95f0c64321f3c00b6806c583ad537

Observation 1e9c5fe6-792f-4a08-87fe-763072c2dce9 · outbound

This paper cites Deliberate then Generate: Enhanced Prompting Framework for Text Generation.

Refining Answer Distributions for Improved Large Language Model Reasoning Deliberate then Generate: Enhanced Prompting Framework for Text Generation

Reference 2024

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Pith citing papers

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