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Paper Citation Record · LEDGER

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning

As of 7 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2505.22591.

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

pith.paper-citation-record.v1
2505.22591 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:08:02.963798Z

measured 22 of 22 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

22 of 22 outbound references displayed

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Outbound references

Observation d4a26916-74ba-4acc-9d04-fa29bc26db40 · outbound

This paper cites WAPITI: A Watermark for Finetuned Open-Source LLMs.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning WAPITI: A Watermark for Finetuned Open-Source LLMs

Reference 3

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Observation 849d6cb3-714c-4455-91d9-b5ca02477092 · outbound

This paper cites The Llama 3 Herd of Models.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning The Llama 3 Herd of Models

Reference 5

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Observation ebf3f1b9-6d06-4d01-93fa-948034e32df2 · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning Measuring Mathematical Problem Solving With the MATH Dataset

Reference 6

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Observation eafc6521-22a9-45fc-a2d6-61a608cbb15d · outbound

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

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning LoRA: Low-Rank Adaptation of Large Language Models

Reference 7

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Observation feceda32-a909-40aa-9d40-372a7b2558f4 · outbound

This paper cites InFindings of the Association for Computational Linguistics: ACL 2024, pages 6498–6526, Bangkok, Thailand.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning InFindings of the Association for Computational Linguistics: ACL 2024, pages 6498–6526, Bangkok, Thailand

Reference 9

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation bd5b2807-5380-4afa-b7fd-cb19bde98ccd · outbound

This paper cites On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey

Reference 10

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Observation a92a3efb-963a-4f6c-86c7-43d92db4a08f · outbound

This paper cites https://openai.com/o1/.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning https://openai.com/o1/

Reference 11

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation eb6d4b1a-1961-466b-87e4-b822fe294ef0 · outbound

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

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 12

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Observation 8c64b116-6d76-463a-a6d4-d8a59049c6f0 · outbound

This paper cites Does Synthetic Data Generation of LLMs Help Clinical Text Mining?.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning Does Synthetic Data Generation of LLMs Help Clinical Text Mining?

Reference 13

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Observation b60ab45a-17f9-4a91-aa56-43fdc2decc3a · outbound

This paper cites MathScale: Scaling Instruction Tuning for Mathematical Reasoning.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning MathScale: Scaling Instruction Tuning for Mathematical Reasoning

Reference 14

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Observation d3a7b24f-d4e0-4636-a7cb-5df2db9c8be1 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning Gemini: A Family of Highly Capable Multimodal Models

Reference 15

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Observation cb9f8a6f-9767-4edf-a3d1-afd94ad24560 · outbound

This paper cites UAlign: Leveraging Uncertainty Estimations for Factuality Alignment on Large Language Models.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning UAlign: Leveraging Uncertainty Estimations for Factuality Alignment on Large Language Models

Reference 16

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Observation 9f1c2a84-267f-40c4-8045-54b173d5138e · outbound

This paper cites Improving Factual Consistency for Knowledge-Grounded Dialogue Systems via Knowledge Enhancement and Alignment.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning Improving Factual Consistency for Knowledge-Grounded Dialogue Systems via Knowledge Enhancement and Alignment

Reference 17

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Observation 8d5a1a9f-cb02-4890-b00f-91d428eb60cd · outbound

This paper cites Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement

Reference 18

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Observation d066fce4-9fef-4197-9680-5a30405d89a7 · outbound

This paper cites InFindings of the Association for Compu- tational Linguistics: EMNLP 2024, pages 11185– 11208, Miami, Florida, USA.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning InFindings of the Association for Compu- tational Linguistics: EMNLP 2024, pages 11185– 11208, Miami, Florida, USA

Reference 19

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 95bdd5df-221f-4d22-8a4a-88ac65c41668 · outbound

This paper cites Evaluating the Performance of Large Language Models on GAOKAO Benchmark.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 20

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Observation b1b3b95f-c116-44d1-bbe9-8548a23a67f7 · outbound

This paper cites In Findings of the Association for Computational Lin- guistics: NAACL 2024, pages 2299–2314, Mexico City, Mexico.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning In Findings of the Association for Computational Lin- guistics: NAACL 2024, pages 2299–2314, Mexico City, Mexico

Reference 21

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Observation 81b1bf14-92db-42da-9a23-ebea48c01e1e · outbound

This paper cites LIMA: Less Is More for Alignment.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning LIMA: Less Is More for Alignment

Reference 22

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Observation 7c19570d-656b-4a68-8184-6a38aa8373f6 · outbound

This paper cites Language Models are Few-Shot Learners.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning Language Models are Few-Shot Learners

Reference 2020

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Observation 1b63f068-ec41-4d26-af1a-e6a1344482e3 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning Training Verifiers to Solve Math Word Problems

Reference 2021

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Observation c8dad2d9-b65a-4036-95d4-d2da58b2f223 · outbound

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Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning Mistral 7B

Reference 2023

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Observation f06ddb18-3750-4f8e-b5f6-a6a00d13f4f7 · outbound

This paper cites Learning From Mistakes Makes LLM Better Reasoner.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning Learning From Mistakes Makes LLM Better Reasoner

Reference 2024

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