Tootfinder

New VLT image shows supernova remnant 0509-67.5, the expanding remains of a star that exploded hundreds of years ago in a double detonation-- the first photographic evidence that stars can die with two blasts https://phys.org/news/2025-07-detonation-image-star-de…

Double detonation: New image shows remains of star destroyed by pair of explosions
For the first time, astronomers have obtained visual evidence that a star met its end by detonating twice. By studying the centuries-old remains of supernova SNR 0509-67.5 with the European Southern Observatory's Very Large Telescope (ESO's VLT), they have found patterns that confirm its star suffered a pair of explosive blasts.

Epitome: Pioneering an Experimental Platform for AI-Social Science Integration
Jingjing Qu, Kejia Hu, Jun Zhu, Wenhao Li, Teng Wang, Zhiyun Chen, Yulei Ye, Chaochao Lu, Aimin Zhou, Xiangfeng Wang, James Evan
https://arxiv.org/abs/2507.01061

Epitome: Pioneering an Experimental Platform for AI-Social Science Integration
The integration of Large Language Models (LLMs) into social science experiments represents a transformative approach to understanding human-AI interactions and their societal impacts. We introduce Epitome, the world's first open experimental platform dedicated to the deep integration of artificial intelligence and social science. Rooted in theoretical foundations from management, communication studies, sociology, psychology, and ethics, Epitome focuses on the interactive impacts of AI on indivi…

DRAG: Distilling RAG for SLMs from LLMs to Transfer Knowledge and Mitigate Hallucination via Evidence and Graph-based Distillation
Jennifer Chen, Aidar Myrzakhan, Yaxin Luo, Hassaan Muhammad Khan, Sondos Mahmoud Bsharat, Zhiqiang Shen
https://arxiv.org/abs/2506.01954

DRAG: Distilling RAG for SLMs from LLMs to Transfer Knowledge and Mitigate Hallucination via Evidence and Graph-based Distillation
Retrieval-Augmented Generation (RAG) methods have proven highly effective for tasks requiring factual consistency and robust knowledge retrieval. However, large-scale RAG systems consume significant computational resources and are prone to generating hallucinated content from Humans. In this work, we introduce $\texttt{DRAG}$, a novel framework for distilling RAG knowledge from large-scale Language Models (LLMs) into small LMs (SLMs). Our approach leverages evidence- and knowledge graph-based d…

Epidemic dynamics in physical-information-social multilayer networks
Mengshou Wang, Liangrong Peng, Baoguo Jia, Liu Hong
https://arxiv.org/abs/2506.00104 h…

Epidemic dynamics in physical-information-social multilayer networks
During epidemic outbreaks, information dissemination enhances individual protection, while social institutions influence the transmission through measures like government interventions, media campaigns, and hospital resource allocation. Here we develop a tripartite physical-information-social epidemic model and derive the corresponding kinetic equations in different scales by using the Microscopic Markov Chain Approach and mean-field approximations. The basic reproduction number and epidemic th…

Controlling the Spread of Epidemics on Networks with Differential Privacy
Dung Nguyen, Aravind Srinivasan, Renata Valieva, Anil Vullikanti, Jiayi Wu
https://arxiv.org/abs/2506.00745

Controlling the Spread of Epidemics on Networks with Differential Privacy
Designing effective strategies for controlling epidemic spread by vaccination is an important question in epidemiology, especially in the early stages when vaccines are limited. This is a challenging question when the contact network is very heterogeneous, and strategies based on controlling network properties, such as the degree and spectral radius, have been shown to be effective. Implementation of such strategies requires detailed information on the contact structure, which might be sensitiv…

There's no male loneliness epidemic, just people with standards and men who don't want to work on themselves.

This https://arxiv.org/abs/2505.11396 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Finding Counterfactual Evidences for Node Classification
Counterfactual learning is emerging as an important paradigm, rooted in causality, which promises to alleviate common issues of graph neural networks (GNNs), such as fairness and interpretability. However, as in many real-world application domains where conducting randomized controlled trials is impractical, one has to rely on available observational (factual) data to detect counterfactuals. In this paper, we introduce and tackle the problem of searching for counterfactual evidences for the GNN…

A Compartmental Model for Epidemiology with Human Behavior and Stochastic Effects
Christian Parkinson, Weinan Wang
https://arxiv.org/abs/2507.01046 https:/…

A Compartmental Model for Epidemiology with Human Behavior and Stochastic Effects
We propose a compartmental model for epidemiology wherein the population is split into groups with either comply or refuse to comply with protocols designed to slow the spread of a disease. Parallel to the disease spread, we assume that noncompliance with protocols spreads as a social contagion. We begin by deriving the reproductive ratio for a deterministic version of the model, and use this to fully characterize the local stability of disease free equilibrium points. We then append the determ…

This https://arxiv.org/abs/2411.19375 has been replaced.
initial toot: https://mastoxiv.page/@arX…

The Co-evolution of Cooperation and Epidemic Spreading
People's cooperation in adopting protective measures is effective in epidemic control and creates herd immunity as a public good. Similarly, the presence of an epidemic is a driving factor for the formation and improvement of cooperation. Here, we study the coevolution of epidemic dynamics and the public good game as a paradigm of cooperation dynamics. Using simulations and a mean-field description, we show that the presence of an epidemic can promote cooperation even in regimes where cooperati…

The Anatomy of Evidence: An Investigation Into Explainable ICD Coding
Katharina Beckh, Elisa Studeny, Sujan Sai Gannamaneni, Dario Antweiler, Stefan R\"uping
https://arxiv.org/abs/2507.01802

The Anatomy of Evidence: An Investigation Into Explainable ICD Coding
Automatic medical coding has the potential to ease documentation and billing processes. For this task, transparency plays an important role for medical coders and regulatory bodies, which can be achieved using explainability methods. However, the evaluation of these approaches has been mostly limited to short text and binary settings due to a scarcity of annotated data. Recent efforts by Cheng et al. (2023) have introduced the MDACE dataset, which provides a valuable resource containing code ev…