Paper Citation Record · LEDGER

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets

As of 8 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2505.20120.

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

pith.paper-citation-record.v1
2505.20120 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:02:23.407776Z

measured 34 of 34 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 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

34 of 34 outbound references displayed

verified exact1
verified fuzzy7
unresolved26
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 846414cb-cb78-40d3-be63-548d06d1a3c9 · outbound

This paper cites Do large language models know how much they know? arXiv preprint arXiv:2502.19573,.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Do large language models know how much they know? arXiv preprint arXiv:2502.19573,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:20.546754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 920689ac-a165-411e-a590-41de7b25372b · outbound

This paper cites Metacognition and uncert ainty communication in humans and large language models.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Metacognition and uncert ainty communication in humans and large language models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:21.067578Z

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Observation 73a04e71-97bd-46e5-a84f-c82d74d3a4eb · outbound

This paper cites SteerConf: Steering LLMs for Confidence Elicitation.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets SteerConf: Steering LLMs for Confidence Elicitation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:21.155458Z

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Observation f73916f2-6aed-4dc4-bd4f-edaf34e7075b · outbound

This paper cites Adaptive Tool Use in Large Language Models with Meta-Cognition Trigger.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Adaptive Tool Use in Large Language Models with Meta-Cognition Trigger

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:02:23.944067Z

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 9fcc5b0c-ede8-42fe-aa4e-30c2f448355d · outbound

This paper cites How accurately do lar ge language models understand code? arXiv preprint arXiv:2504.04372,.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets How accurately do lar ge language models understand code? arXiv preprint arXiv:2504.04372,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:21.369025Z

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Observation 31957ffe-76cf-4433-a147-387c1e4d259b · outbound

This paper cites LLMs can be easily Confused by Instructional Distractions.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets LLMs can be easily Confused by Instructional Distractions

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:21.440027Z

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

This paper cites What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering.

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

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Observation cae0d4a9-fbef-47e2-bb48-f148c93d47e9 · outbound

This paper cites CLAM: Selective Clarification for Ambiguous Questions with Generative Language Models.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets CLAM: Selective Clarification for Ambiguous Questions with Generative Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:21.629631Z

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Observation 8e5f661e-1df7-4c21-b0f1-6e0f8d337875 · outbound

This paper cites How to Train Data-Efficient LLMs.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets How to Train Data-Efficient LLMs

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:21.726501Z

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Observation d6518405-8c50-4c41-8201-8c4225a22de6 · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:21.839046Z

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Observation 3fa6c7f4-9662-44a4-8ec6-8b411930cfbc · outbound

This paper cites When More is Less: Understanding Chain-of-Thought Length in LLMs.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets When More is Less: Understanding Chain-of-Thought Length in LLMs

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:21.918829Z

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Observation 9e977d5c-14fa-49b6-9d43-6817eb2b1691 · outbound

This paper cites Explore Theory of Mind: Program-guided adversarial data generation for theory of mind reasoning.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Explore Theory of Mind: Program-guided adversarial data generation for theory of mind reasoning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:22.077210Z

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Observation 822582f7-0c6d-429d-9f80-a40485da0b2b · outbound

This paper cites A Survey of Theory of Mind in Large Language Models: Evaluations, Representations, and Safety Risks.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets A Survey of Theory of Mind in Large Language Models: Evaluations, Representations, and Safety Risks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:22.194525Z

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Observation 32d0ce56-61ec-4f7a-b3ad-a44e769f6b15 · outbound

This paper cites Strategic Reasoning with Language Models.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Strategic Reasoning with Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:22.291831Z

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Observation fc883aa2-1fb8-4006-8d27-316c761c4e73 · outbound

This paper cites Game-theoretic LLM: Agent Workflow for Negotiation Games.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Game-theoretic LLM: Agent Workflow for Negotiation Games

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:22.366197Z

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Observation cc9f7743-f87c-4dd4-92b1-1cfc14760251 · outbound

This paper cites Werewolf Arena: A Case Study in LLM Evaluation via Social Deduction.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Werewolf Arena: A Case Study in LLM Evaluation via Social Deduction

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:22.412122Z

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Observation 88021d7b-e452-448c-8d7b-ac1311f3bf29 · outbound

This paper cites Joon Sung Park, Joseph O’Brien, Carrie Jun Cai, Meredith Rin gel Morris, Percy Liang, and Michael S Bern- stein.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Joon Sung Park, Joseph O’Brien, Carrie Jun Cai, Meredith Rin gel Morris, Percy Liang, and Michael S Bern- stein

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:22.507476Z

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Observation 00736b61-2dbf-4cdd-a8fc-d78634cf2ab1 · outbound

This paper cites TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets TradingGPT: Multi-Agent System with Layered Memory and Distinct Characters for Enhanced Financial Trading Performance

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:22.596425Z

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Observation 273ba167-799a-4a6b-8fd2-261c3b33c3fd · outbound

This paper cites Systematic biases in llm simulations of debates.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Systematic biases in llm simulations of debates

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:02:24.768222Z

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 aa62b80b-494c-46b2-8175-d02f3ef47a82 · outbound

This paper cites Michael L Littman.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Michael L Littman

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:02:24.674327Z

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 ed3a4d43-6e56-4e31-a840-ac9f9a8909b8 · outbound

This paper cites GameBench: Evaluating Strategic Reasoning Abilities of LLM Agents.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets GameBench: Evaluating Strategic Reasoning Abilities of LLM Agents

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:23.124422Z

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Observation 5452c525-202c-4d5b-a57b-5e80d9ae04d4 · outbound

This paper cites TMGBench: A Systematic Game Benchmark for Evaluating Strategic Reasoning Abilities of LLMs.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets TMGBench: A Systematic Game Benchmark for Evaluating Strategic Reasoning Abilities of LLMs

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:23.225690Z

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Observation 94b5d722-5641-4dcf-a941-3e0c852853cc · outbound

This paper cites Shh, don't say that! Domain Certification in LLMs.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Shh, don't say that! Domain Certification in LLMs

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:23.291142Z

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Observation 8a63cf29-35dd-463b-81f3-c1d7c07658c4 · outbound

This paper cites Red teaming language models with language models.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Red teaming language models with language models

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:02:24.650874Z

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 9ba78bd7-38a5-4d08-b566-276913e85486 · outbound

This paper cites Emmanuel Ameisen, Jack Lindsey, Adam Pearce, Wes Gurnee, Ni cholas L.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Emmanuel Ameisen, Jack Lindsey, Adam Pearce, Wes Gurnee, Ni cholas L

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:02:24.572595Z

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

Observation e009029d-96a1-497a-8a6f-251019135668 · outbound

This paper cites Herman E Daly.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Herman E Daly

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:02:24.458752Z

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

Observation 692847cf-6e1a-40d0-b9c2-75c467c22aee · outbound

This paper cites s uperstar.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets s uperstar

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:02:24.325047Z

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

Observation 78ce6a55-7ef5-478b-9bfe-1dd7e1757bd0 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Constitutional AI: Harmlessness from AI Feedback

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:23.247450Z

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Observation fa534882-376c-4cde-a853-029899c6ef94 · outbound

This paper cites AI Research Considerations for Human Existential Safety (ARCHES).

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets AI Research Considerations for Human Existential Safety (ARCHES)

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:23.266688Z

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Observation 1814f7a2-bf6f-418c-8c18-2b90ea161c3e · outbound

This paper cites I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:21.006903Z

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Observation 4eb170b8-50d4-49a8-a56a-b56e7ccf51fd · outbound

This paper cites On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency, pages 610–623,.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency, pages 610–623,

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:02:24.911579Z

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 511e5e67-f418-4f24-aabe-ffb38ac56a51 · outbound

This paper cites OS-Copilot: Towards Generalist Computer Agents with Self-Improvement.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets OS-Copilot: Towards Generalist Computer Agents with Self-Improvement

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:21.847054Z

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Observation bc85b7a6-98da-4b07-b620-603728842899 · outbound

This paper cites Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:20.433855Z

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Observation ce32099b-bc90-4921-8ac9-bbe955ef44b3 · outbound

This paper cites Language Models (Mostly) Know What They Know.

Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets Language Models (Mostly) Know What They Know

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:20.725474Z

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Pith citing papers

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