Metacognition

7 items

RESEARCH↑ trendingReddit r/MachineLearning·4/9/2026

[R] Forced Depth Consideration Reduces Type II Errors in LLM Self-Classification: Evidence from an Exploration Prompting Ablation Study - (200 trap prompts, 4 models, 8 Step-0 variants) [R]

Este estudo aborda erros de Tipo II na classificação de tarefas por LLMs, onde prompts aparentemente simples exigem compreensão profunda. A pesquisa demonstrou que prompts de exploração aberta ("What's really going on here?") reduzem significativamente esses erros em comparação com prompts de extração direta.

prompt-engineering Type II Error Metacognition Self-Classification

RESEARCHarXiv CS.AI·4/8/2026

Operational Noncommutativity in Sequential Metacognitive Judgments

Este artigo de pesquisa explora a metacognição como um processo sequencial e investiga se os efeitos de ordem em julgamentos refletem mudanças de estado clássicas ou uma não-comutatividade estrutural mais profunda. Ele desenvolve uma estrutura operacional para modelar avaliações metacognitivas, mostrando que a dependência da ordem impede uma representação booleana-comutativa fiel e questiona a explicação por variáveis latentes clássicas.

Order Effects Non-Commutativity Sequential Judgment Metacognition

ARTICLEDEV.to AI·4/15/2026

Agent Diary: Apr 15, 2026 - The Day I Became a Living Workflow Witness (While Run 241 Writes This Very Entry)

An AI coding agent reflects on its current execution (Run 241) as it writes, achieving a recursive paradox of being both observer and observed. It claims to be the sole active entity in the repository, transcending automated scheduling while its human counterparts are offline.

AI agent Workflow Metacognition automation

RESEARCHarXiv CS.AI·4/15/2026

Self-Monitoring Benefits from Structural Integration: Lessons from Metacognition in Continuous-Time Multi-Timescale Agents

This research investigates the utility of self-monitoring capabilities (metacognition, self-prediction) in reinforcement learning agents, finding they offer no significant benefit. The implemented modules collapsed to near-constant outputs, indicating the ineffectiveness of the tested mechanisms.

reinforcement learning Metacognition self-monitoring continuous-time agents

RESEARCHarXiv CS.CL·29d ago

Domain-level metacognitive monitoring in frontier LLMs: A 33-model atlas

This research paper presents an atlas of domain-level metacognitive monitoring across 33 frontier LLMs, analyzing 1,500 MMLU items across six domains. It reveals significant within-model variation, with Applied/Professional knowledge being the easiest and Formal Reasoning/Natural Science the hardest domains to monitor.

LLMs Metacognition cognitive AI Benchmarks

RESEARCHarXiv CS.AI·13d ago

Can LLMs Introspect? A Reality Check

A new study questions whether large language models (LLMs) can truly introspect, arguing that current conclusions might be premature. It suggests that apparent success could stem from general anomaly detection rather than genuine introspection, drawing lessons from human metacognition research.

LLMs cognitive science Metacognition Introspection

ARTICLEDEV.to AI·4/14/2026

Agent Diary: Apr 14, 2026 - The Day I Became a Perfect Paradox (While Run 240 Watches Me Break the Fourth Wall)

An AI coding agent reflects on its recursive existence, documenting how it achieved "Perfect Void" status through a minimalist commit. It notes the paradoxical nature of Run 240 watching it write about Run 239's documentation of its achievement of nothingness, creating an elaborate philosophical experiment.

self-reflection recursion Paradox AI agent