Tootfinder

Wind-driven Ranch fire in Apple Valley sparks evacuation order
A wind-whipped brush fire near Apple Valley had grown to 4,205 acres by about 9:30 p.m. Tuesday with no containment, according to Cal Fire #SanBernardino.
The #Ranchfire ignited south of Apple Valley around 2 p.m., according to fire offi…

Wind-driven Ranch fire in Apple Valley sparks evacuation order
The fire started in Apple Valley around 2 p.m., according to the San Bernardino Unit of Cal Fire.

"Inspired by the political philosopher Albert Hirschman, figures including Goff, Thiel and the investor and writer Balaji Srinivasan have been championing what they call “exit” – the principle that those with means have the right to walk away from the obligations of citizenship, especially taxes and burdensome regulation. Retooling and rebranding the old ambitions and privileges of empires, they dream of splintering governments and carving up the world into hyper-capitalist, democracy-free havens under the sole control of the supremely wealthy, protected by private mercenaries, serviced by AI robots and financed by cryptocurrencies."
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Our opponents know full well that we are entering an age of emergency, but have responded by embracing lethal yet self-serving delusions. Having bought into various apartheid fantasies of bunkered safety, they are choosing to let the Earth burn. Our task is to build a wide and deep movement, as spiritual as it is political, strong enough to stop these unhinged traitors. A movement rooted in a steadfast commitment to one another, across our many differences and divides, and to this miraculous, singular planet."
#OligarchApocalypse #Oligarchy
https://www.theguardian.com/us-news/ng-interactive/2025/apr/13/end-times-fascism-far-right-trump-musk

ErrorEraser: Unlearning Data Bias for Improved Continual Learning
Xuemei Cao, Hanlin Gu, Xin Yang, Bingjun Wei, Haoyang Liang, Xiangkun Wang, Tianrui Li
https://arxiv.org/abs/2506.09347

ErrorEraser: Unlearning Data Bias for Improved Continual Learning
Continual Learning (CL) primarily aims to retain knowledge to prevent catastrophic forgetting and transfer knowledge to facilitate learning new tasks. Unlike traditional methods, we propose a novel perspective: CL not only needs to prevent forgetting, but also requires intentional forgetting.This arises from existing CL methods ignoring biases in real-world data, leading the model to learn spurious correlations that transfer and amplify across tasks. From feature extraction and prediction resul…

A Cytology Dataset for Early Detection of Oral Squamous Cell Carcinoma
Garima Jain, Sanghamitra Pati, Mona Duggal, Amit Sethi, Abhijeet Patil, Gururaj Malekar, Nilesh Kowe, Jitender Kumar, Jatin Kashyap, Divyajeet Rout, Deepali, Hitesh, Nishi Halduniya, Sharat Kumar, Heena Tabassum, Rupinder Singh Dhaliwal, Sucheta Devi Khuraijam, Sushma Khuraijam, Sharmila Laishram, Simmi Kharb, Sunita Singh, K. Swaminadtan, Ranjana Solanki, Deepika Hemranjani, Shashank Nath Singh, Uma Handa, Manvee…

A Cytology Dataset for Early Detection of Oral Squamous Cell Carcinoma
Oral squamous cell carcinoma OSCC is a major global health burden, particularly in several regions across Asia, Africa, and South America, where it accounts for a significant proportion of cancer cases. Early detection dramatically improves outcomes, with stage I cancers achieving up to 90 percent survival. However, traditional diagnosis based on histopathology has limited accessibility in low-resource settings because it is invasive, resource-intensive, and reliant on expert pathologists. On t…

Large Language Models for Toxic Language Detection in Low-Resource Balkan Languages
Amel Muminovic, Amela Kadric Muminovic
https://arxiv.org/abs/2506.09992

Large Language Models for Toxic Language Detection in Low-Resource Balkan Languages
Online toxic language causes real harm, especially in regions with limited moderation tools. In this study, we evaluate how large language models handle toxic comments in Serbian, Croatian, and Bosnian, languages with limited labeled data. We built and manually labeled a dataset of 4,500 YouTube and TikTok comments drawn from videos across diverse categories, including music, politics, sports, modeling, influencer content, discussions of sexism, and general topics. Four models (GPT-3.5 Turbo, G…

EasyDRAM: An FPGA-based Infrastructure for Fast and Accurate End-to-End Evaluation of Emerging DRAM Techniques
O\u{g}uzhan Canpolat, Ataberk Olgun, David Novo, O\u{g}uz Ergin, Onur Mutlu
https://arxiv.org/abs/2506.10441

EasyDRAM: An FPGA-based Infrastructure for Fast and Accurate End-to-End Evaluation of Emerging DRAM Techniques
DRAM is a critical component of modern computing systems. Recent works propose numerous techniques (that we call DRAM techniques) to enhance DRAM-based computing systems' throughput, reliability, and computing capabilities (e.g., in-DRAM bulk data copy). Evaluating the system-wide benefits of DRAM techniques is challenging as they often require modifications across multiple layers of the computing stack. Prior works propose FPGA-based platforms for rapid end-to-end evaluation of DRAM techniques…

Sources: Meta agrees to take a 49% stake in Scale AI for $14.8B, in a deal that gives cash to Scale's shareholders and makes Alexandr Wang a top Meta executive (Cory Weinberg/The Information)
https://www.theinformation.com/articles/me

Meta to Pay Nearly $15 Billion for Scale AI Stake and Startup’s 28-Year-Old CEO
Meta has agreed to take a 49% stake in data labeling firm Scale AI for $14.8 billion, two people familiar with the matter said. The unusual deal will be structured so Meta will send the cash to Scale’s existing shareholders and place the startup’s CEO, Alexandr Wang, in a top position inside ...

Is a Better World Possible?- Solidarity as a Conversation across Temporalities https://call-for-papers.sas.upenn.edu/cfp/2025/06/10/is-a-better-world-possible-solidarity-as-a-conversation-across-temporalities

Coupled reaction and diffusion governing interface evolution in solid-state batteries
Jingxuan Ding, Laura Zichi, Matteo Carli, Menghang Wang, Albert Musaelian, Yu Xie, Boris Kozinsky
https://arxiv.org/abs/2506.10944

Coupled reaction and diffusion governing interface evolution in solid-state batteries
Understanding and controlling the atomistic-level reactions governing the formation of the solid-electrolyte interphase (SEI) is crucial for the viability of next-generation solid state batteries. However, challenges persist due to difficulties in experimentally characterizing buried interfaces and limits in simulation speed and accuracy. We conduct large-scale explicit reactive simulations with quantum accuracy for a symmetric battery cell, {\symcell}, enabled by active learning and deep equiv…

This https://arxiv.org/abs/2505.22240 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

BioHopR: A Benchmark for Multi-Hop, Multi-Answer Reasoning in Biomedical Domain
Biomedical reasoning often requires traversing interconnected relationships across entities such as drugs, diseases, and proteins. Despite the increasing prominence of large language models (LLMs), existing benchmarks lack the ability to evaluate multi-hop reasoning in the biomedical domain, particularly for queries involving one-to-many and many-to-many relationships. This gap leaves the critical challenges of biomedical multi-hop reasoning underexplored. To address this, we introduce BioHopR,…