arXiv:2606. 19728v1 Announce Type: cross Abstract: Infants are well known to develop their motor skills through dense interaction with caregivers.
By Rui Fukushima, Jun Tani
arXiv:2606. 16590v1 Announce Type: cross Abstract: Exploration in deep reinforcement learning (RL) is commonly implemented as temporally uncorrelated white noise.
By Francisco M. L\'opez, Markus R. Ernst, Francisco Cruz, Matej Hoffmann, and Jochen Triesch
arXiv:2604. 09673v2 Announce Type: replace-cross Abstract: The mirror self-recognition test evaluates whether a subject touches a mark on its own body that is visible only in a mirror, and is widely used as an indicator of self-awareness.
By Dongmin Kim, Hoshinori Kanazawa, Yasuo Kuniyoshi
arXiv:2602. 18690v2 Announce Type: replace-cross Abstract: Humans rehearse possible futures offline, as in mental practice and perhaps dreaming, suggesting that world models may support task learning away from the environment.
By Joshua Nunley
arXiv:2607. 23899v1 Announce Type: cross Abstract: This exploratory study examines whether a large multimodal language model, GPT-5.
By Roberto Spinelli, Thiago C. Martins
arXiv:2508. 18066v2 Announce Type: replace-cross Abstract: Controlling high-dimensional and nonlinear musculoskeletal models of the human body is a foundational scientific challenge.
By Boshi An, Alberto Silvio Chiappa, Merkourios Simos, Chengkun Li, Alexander Mathis
arXiv:2607. 13216v1 Announce Type: cross Abstract: Humans recognize movements effortlessly, even from noisy and complex visual input.
By Arefeh Farahmandi, Gunnar Blohm
arXiv:2606. 31943v1 Announce Type: new Abstract: Is the sense of touch a mechanism for human babies' learning of visual concepts?
By Max Whitton, Zecheng Wang, Puchen Liu, Quang Tuan Truong, Shengao Wang, Manaswi Yadamreddy, Oktay Ozel, Visista Jayanti, Saniya Sekhon, Hanna Samuel Tadesse, Lawrence Miao, Junjie Wang, Jiasen Lu, Chen Yu, Boqing Gong
arXiv:2604. 08780v2 Announce Type: replace-cross Abstract: World models promise a paradigm shift in robotics, where an agent learns the physics of its environment once and then acquires behaviors efficiently.
By Mohamad H. Danesh, Chenhao Li, Amin Abyaneh, Anas Houssaini, Kirsty Ellis, Glen Berseth, Marco Hutter, Hsiu-Chin Lin
arXiv:2607. 13560v1 Announce Type: cross Abstract: Recent advances in generative and embodied AI have been driven by large-scale predictive learning over multimodal data.
By Giovanni Pezzulo, Davide Nuzzi, Marco D'Alessandro, Riccardo Proietti, Roberto Bottini, Paul Cisek
arXiv:2605. 26856v2 Announce Type: replace-cross Abstract: We propose the Sensation Modulating Network (SMN): the cognitive agent as the whole body, organized at every scale by opponent dynamics, built from Sensation Modulators -- tissue that senses and acts through one substrate -- paired into Coordinated Action Zones routed by a body-wide broadcast.
By G. Nagarjuna, Durgaprasad Karnam
arXiv:2607. 12114v1 Announce Type: cross Abstract: A humanoid that can walk should not relearn locomotion from scratch to jog or run.
By Kwan-Yee Lin, Zilin Wang, Janelle J. Liu, Stella X. Yu