Paper Citation Record · LEDGER

What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2406.12334.

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

pith.paper-citation-record.v1
2406.12334 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 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 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:02:21.562642Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T22:00:41.512733Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b40e3e17-40fd-43cc-8829-2a2244769ae2 · inbound

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets cites this paper.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:21.562642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f02dd20-f97d-4038-8f17-d0972a1d0d27 · inbound

Evaluating Prompt Engineering Techniques for Accuracy and Confidence Elicitation in Medical LLMs cites this paper.

Evaluating Prompt Engineering Techniques for Accuracy and Confidence Elicitation in Medical LLMs What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T12:44:14.027058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8619f564-aa14-42b3-8b44-b34998980077 · inbound

CEA-LIST at CheckThat! 2025: Evaluating LLMs as Detectors of Bias and Opinion in Text cites this paper.

CEA-LIST at CheckThat! 2025: Evaluating LLMs as Detectors of Bias and Opinion in Text What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T18:42:30.735057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69b5a0ef-14d0-4054-87cb-d1499b3b3125 · inbound

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems cites this paper.

A Conceptual Framework for Requirements Engineering of Pretrained-Model-Enabled Systems What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T16:34:09.624223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f199e73-cd56-421b-91c0-3e0df4fdbbd3 · inbound

Position: Intelligent Coding Systems Should Write Programs with Justifications cites this paper.

Position: Intelligent Coding Systems Should Write Programs with Justifications What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T23:01:59.849579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f040e31f-271f-434e-905f-a6f0fe38d6ab · inbound

Reinforcement Learning for Machine Learning Engineering Agents cites this paper.

Reinforcement Learning for Machine Learning Engineering Agents What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-05T12:24:02.310282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce73f51e-41f1-457e-a692-db9a25da401d · inbound

From scratch to silver: Creating trustworthy training data for patent-SDG classification using Large Language Models cites this paper.

From scratch to silver: Creating trustworthy training data for patent-SDG classification using Large Language Models What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-04T19:27:04.900393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 658d5516-63eb-40d5-8f06-36bb65bf298a · inbound

When the Code Autopilot Breaks: Why LLMs Falter in Embedded Machine Learning cites this paper.

When the Code Autopilot Breaks: Why LLMs Falter in Embedded Machine Learning What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T17:23:21.474317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e4f38a2-3ed7-4f93-a100-f8d063abd32e · inbound

Position: AI Evaluations Should be Grounded on a Theory of Capability cites this paper.

Position: AI Evaluations Should be Grounded on a Theory of Capability What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:00:41.515755Z

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 6dbf4a2b-625a-4177-bcbd-c9427ae46443 · inbound

PIAST: Rapid Prompting with In-context Augmentation for Scarce Training data cites this paper.

PIAST: Rapid Prompting with In-context Augmentation for Scarce Training data What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-16T23:18:40.050451Z

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 9ef101a1-d5e1-4a5b-911a-080263920c69 · inbound

Information-Consistent Language Model Recommendations through Group Relative Policy Optimization cites this paper.

Information-Consistent Language Model Recommendations through Group Relative Policy Optimization What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-16T22:08:36.166115Z

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 b8fb136c-760a-4ab8-af63-520cecba3002 · inbound

Similar Pattern Annotation via Retrieval Knowledge for LLM-Based Test Code Fault Localization cites this paper.

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:00:56.656182Z

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.