Tootfinder

SAVOR: Skill Affordance Learning from Visuo-Haptic Perception for Robot-Assisted Bite Acquisition
Zhanxin Wu, Bo Ai, Tom Silver, Tapomayukh Bhattacharjee
https://arxiv.org/abs/2506.02353

SAVOR: Skill Affordance Learning from Visuo-Haptic Perception for Robot-Assisted Bite Acquisition
Robot-assisted feeding requires reliable bite acquisition, a challenging task due to the complex interactions between utensils and food with diverse physical properties. These interactions are further complicated by the temporal variability of food properties-for example, steak becomes firm as it cools even during a meal. To address this, we propose SAVOR, a novel approach for learning skill affordances for bite acquisition-how suitable a manipulation skill (e.g., skewering, scooping) is for a …

This https://arxiv.org/abs/2502.18744 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

ZEBRA: Leveraging Model-Behavioral Knowledge for Zero-Annotation Preference Dataset Construction
Recent efforts in LLM alignment have focused on constructing large-scale preference datasets via human or Artificial Intelligence (AI) annotators. However, such approaches rely on instance-wise supervision, incurring substantial annotation cost and limited interpretability. In this paper, we propose ZEBRA - a model behavior-wise zero-annotation framework that constructs preference data by leveraging model behavior knowledge derived from benchmark performances. ZEBRA binarizes response pairs by …

Extremely Large-Scale Movable Antenna-Enabled Multiuser Communications: Modeling and Optimization
Min Fu, Lipeng Zhu, Rui Zhang
https://arxiv.org/abs/2506.02735

Extremely Large-Scale Movable Antenna-Enabled Multiuser Communications: Modeling and Optimization
Movable antenna (MA) has been recognized as a promising technology to improve communication performance in future wireless networks such as 6G. To unleash its potential, this paper proposes a novel architecture, namely extremely large-scale MA (XL-MA), which allows flexible antenna/subarray positioning over an extremely large spatial region for effectively enhancing near-field effects and spatial multiplexing performance. In particular, this paper studies an uplink XL-MA-enabled multiuser syste…

Asymptotic convexity of wide and shallow neural networks
Vivek Borkar, Parthe Pandit
https://arxiv.org/abs/2507.01044 https://arxiv.o…

Asymptotic convexity of wide and shallow neural networks
For a simple model of shallow and wide neural networks, we show that the epigraph of its input-output map as a function of the network parameters approximates epigraph of a. convex function in a precise sense. This leads to a plausible explanation of their observed good performance.

Heatables: Effects of Infrared-LED-Induced Ear Heating on Thermal Perception, Comfort, and Cognitive Performance
Valeria Zitz, Michael K\"uttner, Jonas Hummel, Michael T. Knierim, Michael Beigl, Tobias R\"oddiger
https://arxiv.org/abs/2506.02714

Heatables: Effects of Infrared-LED-Induced Ear Heating on Thermal Perception, Comfort, and Cognitive Performance
Maintaining thermal comfort in shared indoor environments remains challenging, as centralized HVAC systems are slow to adapt and standardized to group norms. Cold exposure not only reduces subjective comfort but can impair cognitive performance, particularly under moderate to severe cold stress. Personal Comfort Systems (PCS) have shown promise by providing localized heating, yet many designs target distal body parts with low thermosensitivity and often lack portability. In this work, we invest…

I feel invincible.
I feel like I can make everything.
I finally squeezed some time to lean #freecad. It's awesome.
This is a project that I try to get rid of a proprietary plug from a Technics turntable my grandpa left us.
It's not perfect, but man I feel powerful right now

Empirical Validation of the Independent Chip Model
Juho Kim
https://arxiv.org/abs/2506.00180 https://arxiv.org/pdf/2506.00180

Empirical Validation of the Independent Chip Model
The independent chip model (ICM) forms a cornerstone of all modern poker tournament strategy. However, despite its prominence, the ICM's performance in the real world has not been sufficiently scrutinized, especially at a large scale. In this paper, we introduce our new dataset of poker tournaments, consisting of results of over ten thousand events. Then, using this dataset, we perform two experiments as part of a large-scale empirical validation of the ICM. First, we verify that the ICM perfor…

The last time a Republican-controlled Congress and President Donald Trump moved to slash Medicaid spending, in 2017, a key political force stood in their way:
GOP governors.
Now, as Congress steamrolls toward passing historic Medicaid cuts of about $1 trillion over 10 years through Trump’s tax and spending legislation,
red-state governors are saying little publicly about what it does to health care
— even as they face reductions that will punch multibillion-dollar hole…

GOP Governors Mum as Congress Prepares To Slash Medicaid Spending for Their States - KFF Health News
In 2017, when President Donald Trump tried to repeal Obamacare and roll back Medicaid coverage, Republican governors helped turn Congress against it. Now, as Trump tries again to scale back Medicaid, Republican governors — whose constituents stand to lose federal funding and health coverage — have gone quiet on the health consequences.

Self-ensemble: Mitigating Confidence Distortion for Large Language Models
Zicheng Xu, Guanchu Wang, Guangyao Zheng, Yu-Neng Chuang, Alexander Szalay, Xia Hu, Vladimir Braverman
https://arxiv.org/abs/2506.01951

Self-ensemble: Mitigating Confidence Distortion for Large Language Models
Although Large Language Models (LLMs) perform well in general fields, they exhibit a confidence distortion problem on multi-choice question-answering (MCQA), particularly as the number of answer choices increases. Specifically, on MCQA with many choices, LLMs suffer from under-confidence in correct predictions and over-confidence in incorrect ones, leading to a substantially degraded performance. To solve this problem, we propose Self-ensemble in this work. Our method splits the choices into se…

messal_shale: Messel Shale food web (2014)
A network of feeling links among taxa based on the 48 million years old uppermost early Eocene Messel Shale. Edge property 'certainty' denotes the certainty of the edge. Metadata include evidence, habitat, and trophic roles. The edge direction goes from consumer to resource.
This network has 700 nodes and 6444 edges.
Tags: Biological, Food Web, Uncertain, Weighted, Metadata