Paper Citation Record · LEDGER

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors?

As of 17 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2508.16729.

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

pith.paper-citation-record.v1
2508.16729 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:14:15.826857Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

16 of 16 outbound references displayed

verified exact3
verified fuzzy0
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a23d37d4-00b8-46de-98e7-b3567b0109b0 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? Training Verifiers to Solve Math Word Problems

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T17:14:14.871589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 015b9d05-6afb-494b-987e-2466139f335c · outbound

This paper cites Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine Text.

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine Text

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T17:14:14.909542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f668350f-084c-478b-9070-f1f70689872b · outbound

This paper cites Towards Automated Error Analysis: Learning to Characterize Errors.

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? Towards Automated Error Analysis: Learning to Characterize Errors

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-05T17:14:16.305817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3900cef5-523c-42da-a6af-0a85bf44899c · outbound

This paper cites OpenAGI: When LLM Meets Domain Experts.

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? OpenAGI: When LLM Meets Domain Experts

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T17:14:15.058933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29804989-35c6-4e4a-9274-3d60e8947459 · outbound

This paper cites Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies.

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T17:14:15.106008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab5e25cb-620f-4a68-bef1-be4661329933 · outbound

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

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? Measuring Mathematical Problem Solving With the MATH Dataset

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T17:14:15.155856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6d9cdea-231d-4cf1-b0ff-31de85702961 · outbound

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

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? Towards Reasoning in Large Language Models: A Survey

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T17:14:15.236080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 027cd335-6448-4ff6-95ba-df29b1514b13 · outbound

This paper cites an unresolved cited work.

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T17:14:15.275434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f896320-4ef1-46a0-a1b5-14ec949f8098 · outbound

This paper cites GPT-4 Technical Report.

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? GPT-4 Technical Report

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T17:14:15.362651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5d16450-7c08-4e51-9030-e0749d641090 · outbound

This paper cites Should We Learn Most Likely Functions or Parameters?.

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? Should We Learn Most Likely Functions or Parameters?

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-05T17:14:16.120586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f244ee9f-7f38-41bc-88bd-c76ce3be8802 · outbound

This paper cites Testing for Overfitting.

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? Testing for Overfitting

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-05T17:14:15.976079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0283cb8d-b918-436e-82af-b0340e88d66a · outbound

This paper cites CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge.

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T17:14:15.559867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2167d58-7e84-41ac-b488-819b8c322582 · outbound

This paper cites Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting.

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T17:14:15.620708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 457039ce-d875-4749-a935-86f74465670b · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T17:14:15.708306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f50b7e82-a104-4640-850b-81355962e491 · outbound

This paper cites URL: " 'urlintro :=.

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? URL: " 'urlintro :=

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T17:14:15.757609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ad70c61-9b21-44f8-ac69-d1dab0a0f321 · outbound

This paper cites write newline.

Error Reflection Prompting: Can Large Language Models Successfully Understand Errors? write newline

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T17:14:15.826857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.