Paper Citation Record · LEDGER

Meta Prompting for AI Systems

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2311.11482.

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

pith.paper-citation-record.v1
2311.11482 v10

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

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

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:42:48.835042Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

5
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a2bf41f0-39e9-44a7-964c-d7055b8538fb · inbound

Training and Evaluating Language Models with Template-based Data Generation cites this paper.

Training and Evaluating Language Models with Template-based Data Generation Meta Prompting for AI Systems

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-08-05T01:33:12.225533Z

Source-reported events for the cited work

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

Observation 15f05959-4f7b-413e-983e-5bf038ca28d5 · inbound

From System 1 to System 2: A Survey of Reasoning Large Language Models cites this paper.

From System 1 to System 2: A Survey of Reasoning Large Language Models Meta Prompting for AI Systems

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-08-05T01:33:12.225533Z

Source-reported events for the cited work

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

Observation 05fac4f2-faea-4bae-97b8-a36123ed1f91 · inbound

Question Answering under Temporal Conflict: Evaluating and Organizing Evolving Knowledge with LLMs cites this paper.

Question Answering under Temporal Conflict: Evaluating and Organizing Evolving Knowledge with LLMs Meta Prompting for AI Systems

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T05:42:48.835042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae5f4328-5574-4821-9a42-32855bffe670 · inbound

Cognitive Load-Aware Inference: A Neuro-Symbolic Framework for Optimizing the Token Economy of Large Language Models cites this paper.

Cognitive Load-Aware Inference: A Neuro-Symbolic Framework for Optimizing the Token Economy of Large Language Models Meta Prompting for AI Systems

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T21:15:09.359445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d692b6d-919c-4e8a-a7af-200785d89fa1 · inbound

Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial cites this paper.

Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial Meta Prompting for AI Systems

Reference 132

Resolution: unresolved; no resolver link, observed 2026-08-05T04:50:31.985457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb9bd6a4-8081-4915-b756-a452f09218ab · inbound

VulWeaver: Weaving Broken Semantics for Grounded Vulnerability Detection cites this paper.

VulWeaver: Weaving Broken Semantics for Grounded Vulnerability Detection Meta Prompting for AI Systems

Reference 61

Resolution: verified exact; arxiv_id, observed 2026-08-05T01:33:12.225533Z

Source-reported events for the cited work

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

Observation 2477d88b-044a-45c2-9dce-50db0186b053 · inbound

A Two-Stage LLM Framework for Accessible and Verified XAI Explanations cites this paper.

A Two-Stage LLM Framework for Accessible and Verified XAI Explanations Meta Prompting for AI Systems

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-08-05T01:33:12.225533Z

Source-reported events for the cited work

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

Observation e583f0d5-6284-4468-922a-3d6cdb444b82 · inbound

Code for All: Educational Applications of the "Vibe Coding" Hackathon in Programming Education across All Skill Levels cites this paper.

Code for All: Educational Applications of the "Vibe Coding" Hackathon in Programming Education across All Skill Levels Meta Prompting for AI Systems

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-08-05T01:33:12.225533Z

Source-reported events for the cited work

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

Observation fa069486-8741-4de2-b416-0cd11f8be3e0 · inbound

On Fixing Insecure AI-Generated Code through Model Fine-Tuning and Prompting Strategies cites this paper.

On Fixing Insecure AI-Generated Code through Model Fine-Tuning and Prompting Strategies Meta Prompting for AI Systems

Reference 67

Resolution: verified exact; arxiv_id, observed 2026-08-05T01:33:12.225533Z

Source-reported events for the cited work

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

Observation be9952f5-5030-41a5-ac38-677c58604794 · inbound

Characterize Then Distill: Mechanistic Reasoning in Large Output Spaces cites this paper.

Characterize Then Distill: Mechanistic Reasoning in Large Output Spaces Meta Prompting for AI Systems

Reference 124

Resolution: verified exact; arxiv_id, observed 2026-08-05T01:33:12.225533Z

Source-reported events for the cited work

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

Observation 7700c4dc-2d7d-44a1-b199-158b60badfbd · inbound

Concretized Proposition Prompting Resolves Composition-Knowledge Dichotomy in Large Language Models cites this paper.

Concretized Proposition Prompting Resolves Composition-Knowledge Dichotomy in Large Language Models Meta Prompting for AI Systems

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-08-05T01:33:12.225533Z

Source-reported events for the cited work

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