Tootfinder

Ok, predictions for 2026. In my field:
1) A leap forward in embodiment. Something like a robot folding laundry in an apartment it hasn't seen before. Control and safety will not be solved and pose a major headache.
2)The bubble will not burst this year, unless there is an economic downturn from other causes.
3) LLMs trained specifically to manipulate humans (i.e. maximize engagement games. social media) will become a serious problem.

Trajectory Conditioned Cross-embodiment Skill Transfer
YuHang Tang, Yixuan Lou, Pengfei Han, Haoming Song, Xinyi Ye, Dong Wang, Bin Zhao
https://arxiv.org/abs/2510.07773 https:/…

Trajectory Conditioned Cross-embodiment Skill Transfer
Learning manipulation skills from human demonstration videos presents a promising yet challenging problem, primarily due to the significant embodiment gap between human body and robot manipulators. Existing methods rely on paired datasets or hand-crafted rewards, which limit scalability and generalization. We propose TrajSkill, a framework for Trajectory Conditioned Cross-embodiment Skill Transfer, enabling robots to acquire manipulation skills directly from human demonstration videos. Our key …

The Contingencies of Physical Embodiment Allow for Open-Endedness and Care
Leonardo Christov-Moore (Institute for Advanced Consciousness Studies, Santa Monica, CA), Arthur Juliani (Institute for Advanced Consciousness Studies, Santa Monica, CA), Alex Kiefer (Institute for Advanced Consciousness Studies, Santa Monica, CA, VERSES, Monash Centre for Consciousness and Contemplative Studies), Nicco Reggente (Institute for Advanced Consciousness Studies, Santa Monica, CA), B. Scott Rousse (A…

The Contingencies of Physical Embodiment Allow for Open-Endedness and Care
Physical vulnerability and mortality are often seen as obstacles to be avoided in the development of artificial agents, which struggle to adapt to open-ended environments and provide aligned care. Meanwhile, biological organisms survive, thrive, and care for each other in an open-ended physical world with relative ease and efficiency. Understanding the role of the conditions of life in this disparity can aid in developing more robust, adaptive, and caring artificial agents. Here we define two m…

Embodied Natural Language Interaction (NLI): Speech Input Patterns in Immersive Analytics
Hyemi Song, Matthew Johnson, Kirsten Whitley, Eric Krokos, Amitabh Varshney
https://arxiv.org/abs/2510.12156

Embodied Natural Language Interaction (NLI): Speech Input Patterns in Immersive Analytics
Embodiment shapes how users verbally express intent when interacting with data through speech interfaces in immersive analytics. Despite growing interest in Natural Language Interaction (NLI) for visual analytics in immersive environments, users' speech patterns and their use of embodiment cues in speech remain underexplored. Understanding their interplay is crucial to bridging the gap between users' intent and an immersive analytic system. To address this, we report the results from 15 partici…

I would think Robbo for Kerkez at the half is a must. Still risky against Amad’s speed, but Kerkez is a liability right now. The completely whiffed slide tackle late in the half was the embodiment of his messy gambling.
Mac Allister still struggling and I would bring Curtis Jones on too. Concerns about his head injury, sure, but he’s struggled for form all season.
And this would be a fine time for Salah to get right.
There has been good stuff, too, lost by poor or unlucky f…

"In a world beset by war, genocide, systemic discrimination, and climate catastrophe, we need good news. Donyelle McCray offers the opportunity to hear and see the embodiment of good news emanating from marginalized voices—especially Black women, laypeople, artists, and activists."
From the Christian Century review of the new book by YDS professor Donyelle McCray, "Is it a Sermon?"

Preaching outside the box
Donyelle McCray takes readers on a tour of the edges of homiletics, exploring Black Americans’ gospel proclamation in various...

Cross-Embodiment Dexterous Hand Articulation Generation via Morphology-Aware Learning
Heng Zhang, Kevin Yuchen Ma, Mike Zheng Shou, Weisi Lin, Yan Wu
https://arxiv.org/abs/2510.06068

Cross-Embodiment Dexterous Hand Articulation Generation via Morphology-Aware Learning
Dexterous grasping with multi-fingered hands remains challenging due to high-dimensional articulations and the cost of optimization-based pipelines. Existing end-to-end methods require training on large-scale datasets for specific hands, limiting their ability to generalize across different embodiments. We propose an eigengrasp-based, end-to-end framework for cross-embodiment grasp generation. From a hand's morphology description, we derive a morphology embedding and an eigengrasp set. Conditio…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[14/14]:
- The Contingencies of Physical Embodiment Allow for Open-Endedness and Care
Christov-Moore, Juliani, Kiefer, Reggente, Rousse, Safron, Hinrichs, Polani, Damasio

"Demokratische Kultur entsteht durch Übung. Jedes Gespräch, das von aufmerksamem Zuhören und aufrichtigem Sprechen geprägt ist, ist ein kleiner Schritt hin zu einer menschlicheren, inklusiveren und effektiveren Demokratie."
Josef Merk
#SprechenUndZuhören
#DemokratieStärken

Bridging Political Divides Through Democratic Dialogue: The »Speaking & Listening« Approach in Germany — Democracy & Belonging Forum
It is important to oppose authoritarian populism with fact-checking and critique, but we believe it is also crucial to pursue a positive, alternative vision. For us, this vision is an embodiment of democratic values, best expressed by the narrative: “Even when I strongly disagree with your opinion,

T(R,O) Grasp: Efficient Graph Diffusion of Robot-Object Spatial Transformation for Cross-Embodiment Dexterous Grasping
Xin Fei, Zhixuan Xu, Huaicong Fang, Tianrui Zhang, Lin Shao
https://arxiv.org/abs/2510.12724

T(R,O) Grasp: Efficient Graph Diffusion of Robot-Object Spatial Transformation for Cross-Embodiment Dexterous Grasping
Dexterous grasping remains a central challenge in robotics due to the complexity of its high-dimensional state and action space. We introduce T(R,O) Grasp, a diffusion-based framework that efficiently generates accurate and diverse grasps across multiple robotic hands. At its core is the T(R,O) Graph, a unified representation that models spatial transformations between robotic hands and objects while encoding their geometric properties. A graph diffusion model, coupled with an efficient inverse…

Perspectives and Questions: Toward an Expansive Agenda for Particle Physics
Chris Quigg
https://arxiv.org/abs/2510.06348 https://arxiv.org/pdf/2510.06348…

Perspectives and Questions: Toward an Expansive Agenda for Particle Physics
Global celebration greeted the 2012 discovery at CERN's Large Hadron Collider of a particle that matches the textbook description of the Higgs boson. That achievement validated a remarkable chain of theoretical reasoning that combined the prescriptive notion of electroweak gauge symmetry with a simple, but \emph{ad hoc}, embodiment of spontaneous symmetry breaking. It was made possible by generational triumphs of accelerator art and experimental technique, and by human resourcefulness and colla…

Pretraining in Actor-Critic Reinforcement Learning for Robot Motion Control
Jiale Fan, Andrei Cramariuc, Tifanny Portela, Marco Hutter
https://arxiv.org/abs/2510.12363 https://

Pretraining in Actor-Critic Reinforcement Learning for Robot Motion Control
The pretraining-finetuning paradigm has facilitated numerous transformative advancements in artificial intelligence research in recent years. However, in the domain of reinforcement learning (RL) for robot motion control, individual skills are often learned from scratch despite the high likelihood that some generalizable knowledge is shared across all task-specific policies belonging to a single robot embodiment. This work aims to define a paradigm for pretraining neural network models that enc…

Glovity: Learning Dexterous Contact-Rich Manipulation via Spatial Wrench Feedback Teleoperation System
Yuyang Gao, Haofei Ma, Pai Zheng
https://arxiv.org/abs/2510.09229 https://…

Glovity: Learning Dexterous Contact-Rich Manipulation via Spatial Wrench Feedback Teleoperation System
We present Glovity, a novel, low-cost wearable teleoperation system that integrates a spatial wrench (force-torque) feedback device with a haptic glove featuring fingertip Hall sensor calibration, enabling feedback-rich dexterous manipulation. Glovity addresses key challenges in contact-rich tasks by providing intuitive wrench and tactile feedback, while overcoming embodiment gaps through precise retargeting. User studies demonstrate significant improvements: wrench feedback boosts success rate…

NovaFlow: Zero-Shot Manipulation via Actionable Flow from Generated Videos
Hongyu Li, Lingfeng Sun, Yafei Hu, Duy Ta, Jennifer Barry, George Konidaris, Jiahui Fu
https://arxiv.org/abs/2510.08568

NovaFlow: Zero-Shot Manipulation via Actionable Flow from Generated Videos
Enabling robots to execute novel manipulation tasks zero-shot is a central goal in robotics. Most existing methods assume in-distribution tasks or rely on fine-tuning with embodiment-matched data, limiting transfer across platforms. We present NovaFlow, an autonomous manipulation framework that converts a task description into an actionable plan for a target robot without any demonstrations. Given a task description, NovaFlow synthesizes a video using a video generation model and distills it in…