Tootfinder

sp_colocation: Social co-locations (2018)
Network of colocations between peoople, based on the information on which RFID readers received information from the RFID tags. Namely, we define two individuals to be in co-presence if the same exact set of readers have received signals from both individuals during a 20s time window.
This network has 81 nodes and 150126 edges.
Tags: Social, Offline, Unweighted, Weighted, Temporal, Metadata

Things I enjoy: adding a new ring address across the cluster. Since I added the migration network post-cluster creation it couldn't being used by `corosync` in case something tragic happened. Also, it meant that if you added a new node to the cluster it wouldn't verify that the migration network was online on the new node when it brought it into the cluster. However, solved that pretty fast by just adding it as a `ringX` entry (in this case `ring3`) to all the nodes and enabled it…

Policy-Based Trajectory Clustering in Offline Reinforcement Learning
Hao Hu, Xinqi Wang, Simon Shaolei Du
https://arxiv.org/abs/2506.09202 https://

Policy-Based Trajectory Clustering in Offline Reinforcement Learning
We introduce a novel task of clustering trajectories from offline reinforcement learning (RL) datasets, where each cluster center represents the policy that generated its trajectories. By leveraging the connection between the KL-divergence of offline trajectory distributions and a mixture of policy-induced distributions, we formulate a natural clustering objective. To solve this, we propose Policy-Guided K-means (PG-Kmeans) and Centroid-Attracted Autoencoder (CAAE). PG-Kmeans iteratively trains…

Cancer cells use cholesterol armor to survive heat shock treatment, study discovers
https://phys.org/news/2025-06-cancer-cells-cholesterol-armor-survive.html#google_vignette

TIL linking likely does not make a program a derivative of a library in the EU, thus making the GPL, LGPL and MPL effectivelly identical here.
https://interoperable-europe.ec.europa.eu/collection/eupl/news/copyleft-or-reciprocal

Cybernetic Marionette: Channeling Collective Agency Through a Wearable Robot in a Live Dancer-Robot Duet
Anup Sathya, Jiasheng Li, Zeyu Yan, Adriane Fang, Bill Kules, Jonathan David Martin, Huaishu Peng
https://arxiv.org/abs/2506.10079

Cybernetic Marionette: Channeling Collective Agency Through a Wearable Robot in a Live Dancer-Robot Duet
We describe DANCE^2, an interactive dance performance in which audience members channel their collective agency into a dancer-robot duet by voting on the behavior of a wearable robot affixed to the dancer's body. At key moments during the performance, the audience is invited to either continue the choreography or override it, shaping the unfolding interaction through real-time collective input. While post-performance surveys revealed that participants felt their choices meaningfully influenced …

Headlines like this really make me want to just give up (by which I mean move to one of those tiny offshore islands in the North Atlantic)
https://theconversation.com/ai-tools-collect-and-store-da…

AI tools collect and store data about you from all your devices – here’s how to be aware of what you’re revealing
AI tools that provide information to you also gather lots of information from you and may provide it to third parties.

Collective Bargaining in the Information Economy Can Address AI-Driven Power Concentration
Nicholas Vincent, Matthew Prewitt, Hanlin Li
https://arxiv.org/abs/2506.10272

Collective Bargaining in the Information Economy Can Address AI-Driven Power Concentration
This position paper argues that there is an urgent need to restructure markets for the information that goes into AI systems. Specifically, producers of information goods (such as journalists, researchers, and creative professionals) need to be able to collectively bargain with AI product builders in order to receive reasonable terms and a sustainable return on the informational value they contribute. We argue that without increased market coordination or collective bargaining on the side of th…

Very excited about this! Code to access GRIN will help lots of Google Books partners, and the example might open other doors, as well as the obvious benefits of access to data!
'Institutional Books 1.0: A 242B token dataset from Harvard Library's collections, refined for accuracy and usability' https://arxiv.org/abs/2506…

Institutional Books 1.0: A 242B token dataset from Harvard Library's collections, refined for accuracy and usability
Large language models (LLMs) use data to learn about the world in order to produce meaningful correlations and predictions. As such, the nature, scale, quality, and diversity of the datasets used to train these models, or to support their work at inference time, have a direct impact on their quality. The rapid development and adoption of LLMs of varying quality has brought into focus the scarcity of publicly available, high-quality training data and revealed an urgent need to ground the steward…

This https://arxiv.org/abs/2504.20349 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…