Paper Citation Record · LEDGER

Meta Prompting for AI Systems

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 22 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 22 of 22 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 22 of 22 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:40:03.510992Z

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 2026-08-20T06:33:59.587034+00:00.

Observation 8c2f2445-033b-4113-a44d-a367fe750229 · inbound

Knowledge prompt chaining for semantic modeling cites this paper.

Knowledge prompt chaining for semantic modeling Meta Prompting for AI Systems

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T20:27:02.140677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e17e28e7-4dac-4703-bbe8-913268f87ce8 · inbound

MASTER: A Multi-Agent System with LLM Specialized MCTS cites this paper.

MASTER: A Multi-Agent System with LLM Specialized MCTS Meta Prompting for AI Systems

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-10T15:19:25.990932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ece74cf4-2100-47cb-bfd8-4a82eceb662f · inbound

Irony Detection, Reasoning and Understanding in Zero-shot Learning cites this paper.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Meta Prompting for AI Systems

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-10T05:55:07.709990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-20T06:33:59.587034+00:00.

Observation a4f509c0-69d8-4213-8bdf-e0319299be9c · inbound

Trusting CHATGPT: how minor tweaks in the prompts lead to major differences in sentiment classification cites this paper.

Trusting CHATGPT: how minor tweaks in the prompts lead to major differences in sentiment classification Meta Prompting for AI Systems

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:03.510992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 430f27d5-38cd-4bbd-9ea5-cdb214a40aaf · inbound

Do Prompt Patterns Affect Code Quality? A First Empirical Assessment of ChatGPT-Generated Code cites this paper.

Do Prompt Patterns Affect Code Quality? A First Empirical Assessment of ChatGPT-Generated Code Meta Prompting for AI Systems

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-16T12:06:01.798330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb791e1d-822a-4803-8060-ce54d6dd512a · inbound

Manipulating Multimodal Agents via Cross-Modal Prompt Injection cites this paper.

Manipulating Multimodal Agents via Cross-Modal Prompt Injection Meta Prompting for AI Systems

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-16T11:55:40.240500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3d9f11a-4af4-4337-9d08-6c8404c7d0e6 · inbound

AI-Driven Scholarly Peer Review via Persistent Workflow Prompting, Meta-Prompting, and Meta-Reasoning cites this paper.

AI-Driven Scholarly Peer Review via Persistent Workflow Prompting, Meta-Prompting, and Meta-Reasoning Meta Prompting for AI Systems

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:59.749972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55fac4bf-df97-4888-88fd-a221ae9ec688 · inbound

ClickSight: Interpreting Student Clickstreams to Reveal Insights on Learning Strategies via LLMs cites this paper.

ClickSight: Interpreting Student Clickstreams to Reveal Insights on Learning Strategies via LLMs Meta Prompting for AI Systems

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T15:21:39.548076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96d9c2d2-7456-4e02-b6d7-4eeddfb85169 · inbound

Scalable, Symbiotic, AI and Non-AI Agent Based Parallel Discrete Event Simulations cites this paper.

Scalable, Symbiotic, AI and Non-AI Agent Based Parallel Discrete Event Simulations Meta Prompting for AI Systems

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-07T13:07:52.574887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff457394-c787-472d-9509-ba4d43638196 · inbound

Unified Game Moderation: Soft-Prompting and LLM-Assisted Label Transfer for Resource-Efficient Toxicity Detection cites this paper.

Unified Game Moderation: Soft-Prompting and LLM-Assisted Label Transfer for Resource-Efficient Toxicity Detection Meta Prompting for AI Systems

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T11:56:57.409692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-20T06:33:59.587034+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 2026-08-20T06:33:59.587034+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 2026-08-20T06:33:59.587034+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 2026-08-20T06:33:59.587034+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 2026-08-20T06:33:59.587034+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 2026-08-20T06:33:59.587034+00:00.

Observation 93597a42-1978-4b6b-95f3-e287663a2d78 · inbound

Detecting Behavioral Changes in Python Refactoring Implementations with Foundation Models cites this paper.

Detecting Behavioral Changes in Python Refactoring Implementations with Foundation Models Meta Prompting for AI Systems

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-11T04:25:27.982393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.