arXiv:2510. 02660v2 Announce Type: replace-cross Abstract: When researchers claim AI systems possess ToM or mental models, they are fundamentally discussing behavioral predictions and bias corrections rather than genuine mental states.
By Xiaoyun Yin, Elmira Zahmat Doost, Shiwen Zhou, Garima Arya Yadav, Jamie C. Gorman
arXiv:2606. 12721v1 Announce Type: new Abstract: Inferring others' beliefs requires more than reading surface signals; it requires tracking who told them what, in what order, and how credibly.
By Nikolos Gurney, Stacy Marsella
arXiv:2608. 13567v1 Announce Type: new Abstract: The human brain exhibits a striking degree of functional specialization, with distinct networks supporting language, formal reasoning, reasoning about other minds, and reasoning about the physical world.
By Pengrui Han, Jacob Andreas, Evelina Fedorenko, Andrea Gregor de Varda
arXiv:2607. 11881v1 Announce Type: cross Abstract: Metacognition is a foundational component of intelligence critical to effective learning, problem solving, decision-making, communication, and more.
By Gabrielle Kaili-May Liu, Areeb Gani, Jacqueline Lu, Jordan Thomas, Mark Steyvers, Arman Cohan
arXiv:2606. 30481v1 Announce Type: cross Abstract: Current large language models are extraordinary statistical engines.
By Ziqin Yuan, Jaymari Chua
arXiv:2509. 14474v3 Announce Type: replace Abstract: The debate around Artificial General Intelligence (AGI) remains open due to two fundamentally different goals: replicating human-level performance versus replicating human-like cognitive processes.
By Meltem Subasioglu, Nevzat Subasioglu
arXiv:2606. 16944v1 Announce Type: new Abstract: Theory of mind (ToM), the capacity to ascribe mental states to others and use those ascriptions for prediction and inference, is widely assumed to be essential for effective human-machine integration.
By Nikolos Gurney
arXiv:2607. 17800v1 Announce Type: new Abstract: Representation is a central concept in modern machine learning, where it usually refers to internal encodings that support learning and generalization.
By Gilad Landau, Aviv Keren
arXiv:2606. 13658v1 Announce Type: new Abstract: This paper examines three recent frameworks for understanding the cognitive and epistemic consequences of artificial intelligence: Tri-System Theory, Thinkframes, and System 0.
By Marianna Bergamaschi Ganapini, Massimo Chiriatti, Enrico Panai, Giuseppe Riva
arXiv:2502. 20502v2 Announce Type: replace Abstract: Recent advances in Artificial Intelligence (AI) have yielded powerful computational models that, by learning from vast amounts of human-generated data, are increasingly posited as approximate models of human cognition.
By Lance Ying, Katherine M. Collins, Lionel Wong, Ilia Sucholutsky, Ryan Liu, Adrian Weller, Tianmin Shu, Thomas L. Griffiths, Joshua B. Tenenbaum
arXiv:2606. 26460v1 Announce Type: new Abstract: AI-based scientific automation is increasingly possible by using agents to generate hypotheses, design experiments, and analyze data.
By Ben Prystawski, Kushin Mukherjee, Daniel Wurgaft, Linas Nasvytis, Michael Y. Li, Noah D. Goodman, Michael C. Frank
arXiv:2608. 16213v1 Announce Type: new Abstract: Intelligence is constituted by \textit{process} (iterative activity through which output emerges), not in the output itself.
By Michael J. Richardson, Ayeh Alhasan, Cassandra Crone, M. Paula Diaz Monfort, Patrick Nalepka, Mark Dras, Rachel W. Kallen, David M. Kaplan