Paper Citation Record · LEDGER

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation

As of 9 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2506.06470.

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

pith.paper-citation-record.v1
2506.06470 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T06:01:49.694046Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T15:26:51.781825Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T10:31:04.030419Z

Reference resolution

50 of 50 outbound references displayed

verified exact0
verified fuzzy24
unresolved25
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e7aacfc1-b571-47ed-b24b-2b7462e771a1 · outbound

This paper cites GPT-4 Technical Report.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation GPT-4 Technical Report

Reference 1

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Observation 27a2278c-5993-44af-885a-70f84c5338be · outbound

This paper cites Self-RAG: Learning to re- trieve, generate, and critique through self-reflection.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Self-RAG: Learning to re- trieve, generate, and critique through self-reflection

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:50.126089Z

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Observation 2a511bd8-673f-43b9-bb86-36006c8bdcb9 · outbound

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

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Graph of thoughts: Solving elaborate problems with large language models

Reference 3

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Observation e81bcf8a-c967-4848-bfb8-61d8cb6aa025 · outbound

This paper cites Byrd, Robert Zinkov, and Nada Amin.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Byrd, Robert Zinkov, and Nada Amin

Reference 4

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Observation 97fb398d-f726-4260-8363-3e2eacb7947c · outbound

This paper cites Large Language Monkeys: Scaling Inference Compute with Repeated Sampling.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Large Language Monkeys: Scaling Inference Compute with Repeated Sampling

Reference 5

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Observation f3f1fca1-093c-4983-ab00-79e831f20474 · outbound

This paper cites Alphamath almost zero: Process supervision without process.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Alphamath almost zero: Process supervision without process

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:50.104437Z

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Observation d04d8f75-798d-4b10-90b1-b436e9db4eae · outbound

This paper cites Divide-and-conquer meets consensus: Unleashing the power of functions in code generation.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Divide-and-conquer meets consensus: Unleashing the power of functions in code generation

Reference 7

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6964d4f8-fdea-4b04-baba-d7a86d172e36 · outbound

This paper cites TheoremQA: A theorem-driven question answering dataset.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation TheoremQA: A theorem-driven question answering dataset

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:50.088217Z

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Observation 97b3ee0f-0e34-4f5f-ba37-f1ccb585f16b · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Training Verifiers to Solve Math Word Problems

Reference 10

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Observation e542f507-00ec-4d11-b3cb-f56b8b06c383 · outbound

This paper cites ToRA: A tool-integrated reasoning agent for mathematical problem solving.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation ToRA: A tool-integrated reasoning agent for mathematical problem solving

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:50.079581Z

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Observation 8eb09dac-5e12-44bc-ada9-c3b04b505730 · outbound

This paper cites The Llama 3 Herd of Models.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation The Llama 3 Herd of Models

Reference 12

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Observation 6615949d-360f-4b61-aafd-d0fa82c3cc12 · outbound

This paper cites Olympiadbench: A challenging benchmark for promoting agi with olympiad-level bilingual multimodal scientific problems.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Olympiadbench: A challenging benchmark for promoting agi with olympiad-level bilingual multimodal scientific problems

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:50.071182Z

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Observation a6206ae8-5c3d-49b4-9454-3b9f7b7dfdd7 · outbound

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

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Measuring mathematical problem solving with the MATH dataset

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:50.063008Z

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Observation 9304a6a1-960c-4815-8029-c7f5c411cc31 · outbound

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SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Unresolved cited work

Reference 15

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Observation 58dafe04-cc7a-4e4f-9f17-aac6769e7b41 · outbound

This paper cites Scaling Laws for Neural Language Models.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Scaling Laws for Neural Language Models

Reference 16

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Observation 5d23a060-1f90-47c6-ae2a-39bdaf4805f3 · outbound

This paper cites Joshi, Hanna Moazam, Heather Miller, Matei Zaharia, and Christopher Potts.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Joshi, Hanna Moazam, Heather Miller, Matei Zaharia, and Christopher Potts

Reference 17

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Observation ca1cde79-0582-48a3-9987-ef2351bf5337 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Adam: A Method for Stochastic Optimization

Reference 18

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Observation e2e395fa-293f-4a74-b642-2dc397fdb872 · outbound

This paper cites Let’s verify step by step.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Let’s verify step by step

Reference 19

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Source-reported events for the cited work

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Observation c5320723-4884-4098-a925-eb61e99e37b8 · outbound

This paper cites Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems

Reference 20

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Observation 894aa066-6ce1-407a-8262-3fd0d77c2a05 · outbound

This paper cites De- ductive verification of chain-of-thought reasoning.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation De- ductive verification of chain-of-thought reasoning

Reference 21

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Observation 845cded4-b15d-4a5f-9945-02bb648920de · outbound

This paper cites Augmenting math word problems via iter- ative question composing.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Augmenting math word problems via iter- ative question composing

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:50.018575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1d994272-1ae9-4e24-b792-01b45293f264 · outbound

This paper cites WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct

Reference 23

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Observation d391c9a1-d796-49d8-b8f1-4b6dd3343939 · outbound

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

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Self-refine: Iterative refine- ment with self-feedback

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:50.010218Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0e5fb33f-a412-4300-96f1-554ec0c7cda3 · outbound

This paper cites Mixed precision training.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Mixed precision training

Reference 25

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Observation 7977b957-b1e6-4d74-80d4-4eac8e9c6d09 · outbound

This paper cites Language model self-improvement by reinforcement learning contemplation.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Language model self-improvement by reinforcement learning contemplation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:49.992891Z

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Observation 04767874-cc53-40d4-8f29-3b2332b46b50 · outbound

This paper cites MathFusion: Enhancing Mathematical Problem-solving of LLM through Instruction Fusion.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation MathFusion: Enhancing Mathematical Problem-solving of LLM through Instruction Fusion

Reference 27

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Observation c9fc2a4a-e911-4326-bb45-84ff21f0a476 · outbound

This paper cites Scaling Language Models: Methods, Analysis & Insights from Training Gopher.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Reference 28

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Observation cd05c8d1-fc17-4466-a809-6e6af6f526ab · outbound

This paper cites Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters

Reference 29

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Source-reported events for the cited work

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Observation 22a82896-b587-4f09-8ad6-543654d08c92 · outbound

This paper cites Analysing mathematical reasoning abilities of neural models.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Analysing mathematical reasoning abilities of neural models

Reference 30

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Source-reported events for the cited work

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Observation d9ed9ac6-d457-4101-959d-acc064a3f801 · outbound

This paper cites Rewarding progress: Scaling automated process verifiers for LLM reasoning.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Rewarding progress: Scaling automated process verifiers for LLM reasoning

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:49.973837Z

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Observation 74731a10-536c-431b-bafd-bb46b566c5ea · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 32

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Observation 7b657d8b-325c-4634-a932-9fccc8102c8a · outbound

This paper cites Mathscale: Scaling instruction tuning for mathematical reasoning.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Mathscale: Scaling instruction tuning for mathematical reasoning

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:49.964749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 70a24f33-f89f-420e-a912-b3f76ef6311f · outbound

This paper cites DeepDistill: Enhancing LLM Reasoning Capabilities via Large-Scale Difficulty-Graded Data Training.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation DeepDistill: Enhancing LLM Reasoning Capabilities via Large-Scale Difficulty-Graded Data Training

Reference 34

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Source-reported events for the cited work

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Observation 6f9294c4-bb5f-4959-afeb-825ce813ab14 · outbound

This paper cites DART-math: Difficulty-aware rejection tuning for mathematical problem-solving.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation DART-math: Difficulty-aware rejection tuning for mathematical problem-solving

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:49.956635Z

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Observation b892089e-e129-442b-83d0-180c10c154bc · outbound

This paper cites Openmathinstruct-2: Accelerating AI for math with massive open-source instruction data.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Openmathinstruct-2: Accelerating AI for math with massive open-source instruction data

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:49.948456Z

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Observation 45fbdd08-ef36-498b-8511-4bc76f5db7f7 · outbound

This paper cites Mathcoder: Seamless code integration in llms for enhanced mathemat- ical reasoning.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Mathcoder: Seamless code integration in llms for enhanced mathemat- ical reasoning

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:49.939948Z

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Observation 933337ac-cda6-4136-ade6-9c7294b793af · outbound

This paper cites Math-shepherd: Verify and reinforce llms step-by-step without human annotations.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Math-shepherd: Verify and reinforce llms step-by-step without human annotations

Reference 38

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Observation ee371d35-76ef-4986-8abf-a571e1c8f312 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Chain-of-thought prompting elicits reasoning in large language models

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:49.926208Z

Source-reported events for the cited work

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Observation 3f1b2dee-12e0-4eea-ac87-090838360a58 · outbound

This paper cites Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T06:01:49.657996Z

Source-reported events for the cited work

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Observation eb26364b-9673-4dc3-92d1-342ae56409e4 · outbound

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

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T06:01:49.661304Z

Source-reported events for the cited work

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Observation bccae710-a182-47cd-93e1-f582b97def4c · outbound

This paper cites Optimizing Chain-of-Thought Reasoners via Gradient Variance Minimization in Rejection Sampling and RL.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Optimizing Chain-of-Thought Reasoners via Gradient Variance Minimization in Rejection Sampling and RL

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T06:01:49.664298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f6473ac-46ea-47f6-b125-57b7ea2d72c0 · outbound

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

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Griffiths, Yuan Cao, and Karthik R Narasimhan

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T06:01:49.667556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f1b7163-dc08-4270-b641-0658e9727f5e · outbound

This paper cites Metamath: Bootstrap your own mathematical questions for large language models.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Metamath: Bootstrap your own mathematical questions for large language models

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T06:01:49.670751Z

Source-reported events for the cited work

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Observation d6c23084-484b-49cc-9614-de44279b59ca · outbound

This paper cites Scaling Relationship on Learning Mathematical Reasoning with Large Language Models.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Scaling Relationship on Learning Mathematical Reasoning with Large Language Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T06:01:49.674191Z

Source-reported events for the cited work

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Observation eff1e131-cff3-42a4-a439-64d4d7de1691 · outbound

This paper cites Optimizing generative ai by backpropagating language model feedback.Nature, 639:609– 616, 2025.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Optimizing generative ai by backpropagating language model feedback.Nature, 639:609– 616, 2025

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:49.907121Z

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Observation f8934e60-64aa-458e-b0d6-d235526a419b · outbound

This paper cites Rest-mcts*: Llm self-training via process reward guided tree search.Advances in Neural Information Processing Systems, 37:64735–64772, 2024.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Rest-mcts*: Llm self-training via process reward guided tree search.Advances in Neural Information Processing Systems, 37:64735–64772, 2024

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T06:01:49.680835Z

Source-reported events for the cited work

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Observation 1f45e870-0fa1-4943-972e-ba6306902764 · outbound

This paper cites Generative verifiers: Reward modeling as next-token prediction.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Generative verifiers: Reward modeling as next-token prediction

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:49.892757Z

Source-reported events for the cited work

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Observation a4b74b54-490a-4d21-a8ad-362f80aeaa36 · outbound

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

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Chain of preference optimization: Improving chain-of-thought reasoning in LLMs

Reference 49

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T06:01:49.882850Z

Source-reported events for the cited work

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Observation 80bb1ffd-0e50-4f9d-93f3-70b224317ae2 · outbound

This paper cites The computation sequence token length was fixed at 4096 to capture long range mathematical rea- soning.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation The computation sequence token length was fixed at 4096 to capture long range mathematical rea- soning

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:49.874125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2316e3fe-bec0-481d-90b0-f1d776bdce3a · outbound

This paper cites Step 2:Use the given altitude length to solve forx.

SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation Step 2:Use the given altitude length to solve forx

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:01:49.864918Z

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Learning from Contrasts: Synthesizing Reasoning Paths from Diverse Search Trajectories cites this paper.

Learning from Contrasts: Synthesizing Reasoning Paths from Diverse Search Trajectories SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:31:04.034080Z

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