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相关论文: Metacognition Should Be the Scientific Framework f…

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Metacognition--the capacity to monitor and evaluate one's own knowledge and performance--is foundational to human decision-making, learning, and communication. As large language models (LLMs) become increasingly embedded in both high-stakes…

人工智能 · 计算机科学 2025-10-14 Mark Steyvers , Megan A. K. Peters

The implementation of responsible AI in an organization is inherently complex due to the involvement of multiple stakeholders, each with their unique set of goals and responsibilities across the entire AI lifecycle. These responsibilities…

计算机与社会 · 计算机科学 2025-07-24 Blaine Kuehnert , Rachel M. Kim , Jodi Forlizzi , Hoda Heidari

Generative Artificial Intelligence (GenAI) constitutes a transformative technological wave that reconfigures industries through its unparalleled capabilities for content creation, reasoning, planning, and multimodal understanding. This…

Collecting and labeling training data is one important step for learning-based methods because the process is time-consuming and biased. For face analysis tasks, although some generative models can be used to generate face data, they can…

计算机视觉与模式识别 · 计算机科学 2023-04-04 Dingyun Zhang , Chenglai Zhong , Yudong Guo , Yang Hong , Juyong Zhang

Generative artificial intelligence (GenAI) holds the potential to transform the delivery, cultivation, and evaluation of human learning. This Perspective examines the integration of GenAI as a tool for human learning, addressing its…

人机交互 · 计算机科学 2024-09-06 Lixiang Yan , Samuel Greiff , Ziwen Teuber , Dragan Gašević

People navigate complex environments using cues, heuristics, and other strategies, which are often adaptive in stable settings. However, as AI increasingly permeates society's information environments, those become more adaptive and…

Agentic Artificial Intelligence (AI) can autonomously pursue long-term goals, make decisions, and execute complex, multi-turn workflows. Unlike traditional generative AI, which responds reactively to prompts, agentic AI proactively…

计算机与社会 · 计算机科学 2025-02-18 Anirban Mukherjee , Hannah Hanwen Chang

Self-recognition is a crucial metacognitive capability for AI systems, relevant not only for psychological analysis but also for safety, particularly in evaluative scenarios. Motivated by contradictory interpretations of whether models…

人工智能 · 计算机科学 2025-10-07 Xiaoyan Bai , Aryan Shrivastava , Ari Holtzman , Chenhao Tan

Complex decision-making by autonomous machines and algorithms could underpin the foundations of future society. Generative AI is emerging as a powerful engine for such transitions. However, we show that Generative AI-driven developments…

机器人学 · 计算机科学 2026-01-15 Le Liu , Bangguo Yu , Nynke Vellinga , Ming Cao

There is an increasing imperative to anticipate and understand the performance and safety of generative AI systems in real-world deployment contexts. However, the current evaluation ecosystem is insufficient: Commonly used static benchmarks…

We present a framework for automating generative deep learning with a specific focus on artistic applications. The framework provides opportunities to hand over creative responsibilities to a generative system as targets for automation. For…

机器学习 · 计算机科学 2021-07-06 Sebastian Berns , Terence Broad , Christian Guckelsberger , Simon Colton

Recent advances in artificial intelligence (AI) have achieved human-scale speed and accuracy for classification tasks. In turn, these capabilities have made AI a viable replacement for many human activities that at their core involve…

人工智能 · 计算机科学 2022-05-24 Hadi Esmaeilzadeh , Reza Vaezi

Effective study strategies fail when preparatory tasks consume learning time. While AI educational tools demonstrate efficacy, understanding how they align with self-regulation needs in authentic study contexts remains limited. We conducted…

人机交互 · 计算机科学 2026-02-17 Hongming Li , Salah Esmaeiligoujar , Nazanin Adham , Hai Li , Rui Huang

Generative Artificial Intelligence (GenAI), specifically large language models (LLMs) like ChatGPT, has swiftly entered organizations without adequate governance, posing both opportunities and risks. Despite extensive debate on GenAI's…

人工智能 · 计算机科学 2026-02-23 Johannes Schneider , Pauline Kuss , Rene Abraham , Christian Meske

This paper introduces the concept of ``generative midtended cognition'', exploring the integration of generative AI with human cognition. The term "generative" reflects AI's ability to iteratively produce structured outputs, while…

人工智能 · 计算机科学 2026-04-21 Xabier E. Barandiaran , Marta Pérez-Verdugo

Self-improving agents aim to continuously acquire new capabilities with minimal supervision. However, current approaches face two key limitations: their self-improvement processes are often rigid, fail to generalize across tasks domains,…

人工智能 · 计算机科学 2025-06-06 Tennison Liu , Mihaela van der Schaar

The rapid adoption of generative artificial intelligence (AI) in educational assessment has created new opportunities for scalable item creation, personalized feedback, and efficient formative evaluation. However, despite advances in…

计算机与社会 · 计算机科学 2026-04-14 Antoun Yaacoub , Zainab Assaghir , Anuradha Kar

A central idea in understanding brains and building artificial intelligence is that structure determines function. Yet, how the brain's complex structure arises from a limited set of genetic instructions remains a key question. The ultra…

神经元与认知 · 定量生物学 2026-01-28 Xingyu Liu , Yubin Li , Guozhang Chen

Generative AI (GenAI) search tools are increasingly used for information seeking, yet their design tends to encourage cognitive offloading, which may lead to passive engagement, selective attention, and informational homogenization.…

人机交互 · 计算机科学 2026-03-23 Anjali Singh , Karan Taneja , Zhitong Guan , Soo Young Rieh

Artificial intelligence (AI) represents a technological upheaval with the potential to change human society. Because of its transformative potential, AI is increasingly becoming subject to regulatory initiatives at the global level. Yet, so…

综合经济学 · 经济学 2023-05-22 Jonas Tallberg , Eva Erman , Markus Furendal , Johannes Geith , Mark Klamberg , Magnus Lundgren