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Paper Citation Record · LEDGER

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models

As of 20 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2607.18266.

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

pith.paper-citation-record.v1
2607.18266 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T13:26:31.446743Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

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measured 0 of 1 external citation measurements

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Reference resolution

34 of 34 outbound references displayed

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  • unresolved32
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Outbound references

Observation 2d74bceb-8c74-4a8e-a0e3-fe72557c4634 · outbound

This paper cites Language models are few-shot learners.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Language models are few-shot learners

Reference 1

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Observation c73d23d9-6651-47d6-b51f-e4bfd815839e · outbound

This paper cites Large language models are zero-shot reasoners.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Large language models are zero-shot reasoners

Reference 2

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Observation 5c05b729-878e-4c2e-b464-3df54e8ebc06 · outbound

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

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Chain-of-thought prompting elicits reasoning in large language models

Reference 3

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Observation fbbbeae7-f193-4c31-bb2f-b5445254fed3 · outbound

This paper cites Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Reference 4

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Observation 64bdffa7-d66d-4c48-b23d-73e480a3bc7b · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive NLP tasks.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Retrieval-augmented generation for knowledge-intensive NLP tasks

Reference 5

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Observation 9eae3084-f10e-40d8-879b-14c55b587595 · outbound

This paper cites Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al

Reference 6

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Observation 58f57867-c9d6-4227-84b9-37c8ca272be2 · outbound

This paper cites Teaching Large Language Models to Reason with Reinforcement Learning.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Teaching Large Language Models to Reason with Reinforcement Learning

Reference 7

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Observation 4f802b78-2985-450d-973d-ab8dcfe8a772 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models LoRA: Low-Rank Adaptation of Large Language Models

Reference 8

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Observation 0d1add19-c7df-4872-9617-3d6105ae9cb5 · outbound

This paper cites Smith, Daniel Khashabi, and Hannaneh Hajishirzi.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Smith, Daniel Khashabi, and Hannaneh Hajishirzi

Reference 10

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Observation e778a641-e7dd-4036-bb12-5351055290eb · outbound

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

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 11

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Observation 53a42404-a072-4a3b-9d53-8e60e16b68ea · outbound

This paper cites LIMA: Less is more for alignment.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models LIMA: Less is more for alignment

Reference 12

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Observation 8449589d-b31e-4c6c-be57-ec0c58eee5dd · outbound

This paper cites Socratic method as an approach to teaching.European Researcher, 111(10):511–517, 2016.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Socratic method as an approach to teaching.European Researcher, 111(10):511–517, 2016

Reference 13

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Observation 193c7d70-dfb7-4e02-a51b-cd5a1c78a0c0 · outbound

This paper cites Reyes, Ron Mhel Francis L.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Reyes, Ron Mhel Francis L

Reference 14

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Observation baaeacc8-534b-4c83-a5ea-162015fb2359 · outbound

This paper cites Metacognition in schools: What does the literature suggest about the effectiveness of teaching metacognition in schools?Educational Review, 71(4): 483–500, 2019.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Metacognition in schools: What does the literature suggest about the effectiveness of teaching metacognition in schools?Educational Review, 71(4): 483–500, 2019

Reference 15

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Observation ab5412fa-ed80-4bff-9858-88f722092665 · outbound

This paper cites The art of SOCRATIC QUESTIONING: Recursive thinking with large language models.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models The art of SOCRATIC QUESTIONING: Recursive thinking with large language models

Reference 16

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Observation 4a3e909d-7143-4bdb-b978-05550a509c8b · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Training Verifiers to Solve Math Word Problems

Reference 17

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Observation 1d496a92-4484-4ed6-95be-2371a8987140 · outbound

This paper cites AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning

Reference 18

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Observation 013e0d6f-fe8e-4b8a-8241-d7a5e8048ae0 · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 19

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Observation eb5c7b01-864d-40f1-8e06-b454084014f5 · outbound

This paper cites Hashimoto.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Hashimoto

Reference 20

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Observation c2859c2c-da61-4cee-9b3a-5ac8500ab965 · outbound

This paper cites MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models

Reference 21

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Observation 43700d97-4615-4ffb-853f-9948a26a58f7 · outbound

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

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct

Reference 22

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Observation c4a0cb52-c021-4851-b149-88af2e93b5d8 · outbound

This paper cites Boundless Socratic Learning with Language Games.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Boundless Socratic Learning with Language Games

Reference 23

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Observation eec80562-c3b4-4813-891b-bd0f76e28163 · outbound

This paper cites MLX LM: Language model training and inference for Apple Silicon, 2024.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models MLX LM: Language model training and inference for Apple Silicon, 2024

Reference 24

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Observation a85614d0-3dd2-4385-97ca-6afc0d496f83 · outbound

This paper cites Qwen3 Technical Report.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Qwen3 Technical Report

Reference 25

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Observation a7d56894-14a9-490e-9615-bda63c03f613 · outbound

This paper cites Decoupled Weight Decay Regularization.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Decoupled Weight Decay Regularization

Reference 26

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Observation 7315fb23-b9ee-41c5-bf3e-66bad5e73c87 · outbound

This paper cites SGDR: Stochastic gradient descent with warm restarts.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models SGDR: Stochastic gradient descent with warm restarts

Reference 27

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Observation 13978cd8-f83f-4a1a-b8e7-da366cf5fdd9 · outbound

This paper cites The Llama 3 Herd of Models.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models The Llama 3 Herd of Models

Reference 28

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Observation d2ee7b01-e7b6-41a1-8b81-23e5e4acbc17 · outbound

This paper cites Mistral 7B.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Mistral 7B

Reference 29

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Observation 7abdd09e-e017-4c6c-998b-bfba325aa19b · outbound

This paper cites Gemma 3 Technical Report.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Gemma 3 Technical Report

Reference 30

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Observation e7e30a22-c411-4c4d-b46f-a293230a6c69 · outbound

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Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Unresolved cited work

Reference 31

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Observation 5ac8046e-10ed-48b1-87df-dc66e9306751 · outbound

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Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Solving general arithmetic word problems

Reference 32

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Observation 710e0980-bdab-47ab-9862-3cab55a0e4a5 · outbound

This paper cites Question:.

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Question:

Reference 2015

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Observation 0dde30b5-29b4-4864-b81a-dd3493eb9ee4 · outbound

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Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models Unresolved cited work

Reference 2022

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Observation 7b2e532f-34e9-42cc-93dc-de119c836789 · outbound

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

Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct

Reference 2023

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Pith citing papers

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