Tootfinder

How about some recent, well, pretty unusual #astronomy papers? Like https://arxiv.org/abs/2507.02162 = Dangerous Questions in Astronomy Education or https://arxiv.org/abs/2508.19984 = Communicating astrobiology and the search for life elsewhere: speculations and promises of a developing scientific field in newspapers, press releases and papers ... or https://arxiv.org/abs/2508.04718 = Quantum panprotopsychism and a consciousness-centered universe

AgentCoMa: A Compositional Benchmark Mixing Commonsense and Mathematical Reasoning in Real-World Scenarios
Lisa Alazraki, Lihu Chen, Ana Brassard, Joe Stacey, Hossein A. Rahmani, Marek Rei
https://arxiv.org/abs/2508.19988

AgentCoMa: A Compositional Benchmark Mixing Commonsense and Mathematical Reasoning in Real-World Scenarios
Large Language Models (LLMs) have achieved high accuracy on complex commonsense and mathematical problems that involve the composition of multiple reasoning steps. However, current compositional benchmarks testing these skills tend to focus on either commonsense or math reasoning, whereas LLM agents solving real-world tasks would require a combination of both. In this work, we introduce an Agentic Commonsense and Math benchmark (AgentCoMa), where each compositional task requires a commonsense r…

Looked at @…'s Signals page (https://creativecommons.org/ai-and-the-commons/cc-signals/) again.
I think this…

CC Signals: A New Social Contract for the Age of AI - Creative Commons
TL;DR – What are CC signals? CC signals are a proposed framework to help content stewards express how they want their works used in AI training—emphasizing reciprocity, recognition, and sustainability in machine reuse. They aim to preserve open knowledge by encouraging responsible AI behavior without limiting innovation. 💗Love it! How can I show my support?…

Conference vignette 👀: #OpenScience is about much more than #OpenData. Presenting unpublished work is also Openness, as social science alumna Dr. Ros Attenborough reminded us. And if you can share that way, then...
In the Presidential symposium, another lab alumnus introduced a mouse protein that massively affected the clock ⏰ . His group found it through an ambitious phosphoproteomic 🧪 candidate selection approach on a cell line 🧫 , looking beyond the canonical idea of the clockwork (TTFL in the jargon). Canonical here means canonised by a Nobel prize.
A good friend from Japan explained in the Q&A that his group had just found the SAME gene in a genetic screen of mice 🐁with altered sleep patterns 🐁💤🛌. We know the clock controls sleep. So, independent evidence across continents.👍
Over dinner they started to coordinate how they would each publish their work. #Science working.

CoCoL: A Communication Efficient Decentralized Collaborative Method for Multi-Robot Systems
Jiaxi Huang, Yan Huang, Yixian Zhao, Wenchao Meng, Jinming Xu
https://arxiv.org/abs/2508.20898

CoCoL: A Communication Efficient Decentralized Collaborative Method for Multi-Robot Systems
Collaborative learning enhances the performance and adaptability of multi-robot systems in complex tasks but faces significant challenges due to high communication overhead and data heterogeneity inherent in multi-robot tasks. To this end, we propose CoCoL, a Communication efficient decentralized Collaborative Learning method tailored for multi-robot systems with heterogeneous local datasets. Leveraging a mirror descent framework, CoCoL achieves remarkable communication efficiency with approxim…

Uncertainty on Display: The Effects of Communicating Confidence Cues in Autonomous Vehicle-Pedestrian Interactions
Yue Luo, Xinyan Yu, Tram Thi Minh Tran, Marius Hoggenmueller
https://arxiv.org/abs/2507.18836

Uncertainty on Display: The Effects of Communicating Confidence Cues in Autonomous Vehicle-Pedestrian Interactions
Uncertainty is an inherent aspect of autonomous vehicle (AV) decision-making, yet it is rarely communicated to pedestrians, which hinders transparency. This study investigates how AV uncertainty can be conveyed through two approaches: explicit communication (confidence percentage displays) and implicit communication (vehicle motion cues), across different confidence levels (high and low). Through a within-subject VR experiment (N=26), we evaluated these approaches in a crossing scenario, assess…

EffiComm: Bandwidth Efficient Multi Agent Communication
Melih Yazgan, Allen Xavier Arasan, J. Marius Z\"ollner
https://arxiv.org/abs/2507.19354 https://

EffiComm: Bandwidth Efficient Multi Agent Communication
Collaborative perception allows connected vehicles to exchange sensor information and overcome each vehicle's blind spots. Yet transmitting raw point clouds or full feature maps overwhelms Vehicle-to-Vehicle (V2V) communications, causing latency and scalability problems. We introduce EffiComm, an end-to-end framework that transmits less than 40% of the data required by prior art while maintaining state-of-the-art 3D object detection accuracy. EffiComm operates on Bird's-Eye-View (BEV) feature m…

Filing your taxes without paying extra for the privilege is apparently too "woke."
https://news.bloombergtax.com/financial-accounting/irs-chief-says-direct-file-is-gone-other-audit-tech-is-coming

IRS Chief Says Direct File Is ‘Gone,’ Other Audit Tech Is Coming
The Biden-era IRS free filing tool, Direct File, is “gone,” IRS Commissioner Billy Long said.

NLKI: A lightweight Natural Language Knowledge Integration Framework for Improving Small VLMs in Commonsense VQA Tasks
Aritra Dutta, Swapnanil Mukherjee, Deepanway Ghosal, Somak Aditya
https://arxiv.org/abs/2508.19724

NLKI: A lightweight Natural Language Knowledge Integration Framework for Improving Small VLMs in Commonsense VQA Tasks
Commonsense visual-question answering often hinges on knowledge that is missing from the image or the question. Small vision-language models (sVLMs) such as ViLT, VisualBERT and FLAVA therefore lag behind their larger generative counterparts. To study the effect of careful commonsense knowledge integration on sVLMs, we present an end-to-end framework (NLKI) that (i) retrieves natural language facts, (ii) prompts an LLM to craft natural language explanations, and (iii) feeds both signals to sVLM…

A conceptual framework for understanding longwave cloud effects on climate sensitivity: #climate sensitivity: https://mpimet.mpg.de/en/communication/detail-view-news-homepage/changes-in-cloud-altitude-have-minimal-impact-on-climate-sensitivity