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@arXiv_csCL_bot@mastoxiv.page
2025-10-15 10:28:41

From Knowledge to Treatment: Large Language Model Assisted Biomedical Concept Representation for Drug Repurposing
Chengrui Xiang, Tengfei Ma, Xiangzheng Fu, Yiping Liu, Bosheng Song, Xiangxiang Zeng
arxiv.org/abs/2510.12181

From Knowledge to Treatment: Large Language Model Assisted Biomedical Concept Representation for Drug Repurposing
Drug repurposing plays a critical role in accelerating treatment discovery, especially for complex and rare diseases. Biomedical knowledge graphs (KGs), which encode rich clinical associations, have been widely adopted to support this task. However, existing methods largely overlook common-sense biomedical concept knowledge in real-world labs, such as mechanistic priors indicating that certain drugs are fundamentally incompatible with specific treatments. To address this gap, we propose LLaDR, …

@axbom@axbom.me
2025-11-15 17:33:25
In one of my first talks about human rights and AI (2022) I used the widespread printing press reference to emphasise that in many cases it supported colonialism.

https://axbom.com/aihr/

This text by Sonja Drimmer really breaks down common printing press misrepresentation. Love it!

htt…
@UP8@mastodon.social
2025-10-16 13:53:47

🕯️Simple casting and heat treatment yields alloy with both strength and ductility
techxplore.com/news/2025-09-si

Simple casting and heat treatment yields alloy with both strength and ductility
In the world of metals, it has long been considered common knowledge that achieving both strength and ductility (the ability to stretch without breaking) at the same time is nearly impossible. When a metal is made stronger, it typically becomes brittle, and when it is made more ductile, it usually loses strength—like a seesaw, where one property increases as the other decreases.

@arXiv_csCV_bot@mastoxiv.page
2025-10-13 10:36:20

PhysToolBench: Benchmarking Physical Tool Understanding for MLLMs
Zixin Zhang, Kanghao Chen, Xingwang Lin, Lutao Jiang, Xu Zheng, Yuanhuiyi Lyu, Litao Guo, Yinchuan Li, Ying-Cong Chen
arxiv.org/abs/2510.09507

PhysToolBench: Benchmarking Physical Tool Understanding for MLLMs
The ability to use, understand, and create tools is a hallmark of human intelligence, enabling sophisticated interaction with the physical world. For any general-purpose intelligent agent to achieve true versatility, it must also master these fundamental skills. While modern Multimodal Large Language Models (MLLMs) leverage their extensive common knowledge for high-level planning in embodied AI and in downstream Vision-Language-Action (VLA) models, the extent of their true understanding of phys…

@arXiv_csPL_bot@mastoxiv.page
2025-10-13 08:33:30

A Multilingual Python Programming Language
Saad Ahmed Bazaz, Mirza Omer Beg
arxiv.org/abs/2510.09591 arxiv.org/pdf/2510.09591

A Multilingual Python Programming Language
All widely used and useful programming languages have a common problem. They restrict entry on the basis of knowledge of the English language. The lack of knowledge of English poses a major hurdle to many newcomers who do not have the resources, in terms of time and money, to learn the English language. Studies show that people learn better in their own language. Therefore, we propose a language transpiler built on top of the Python programming language, called UniversalPython, which allows one…

@hex@kolektiva.social
2025-10-30 21:06:59

I'm especially interested in a few things if anyone is willing to help...
1) missing words and simple typos - My ADHD brain skips words coming out and fulls them in when reading, so it's easy for me to make mistakes and hard for me to catch them.
2) questions - I tend to work from a lot of assumed knowledge, collected from all over, and I'm really trying to make my work more accessible. I assume I'm talking about a bunch of stuff most folks don't know, but I don't know which of them come from some rabbit hole I went down and which are more common knowledge.
3) challenges - I get bored when having things explained to me so I have a tendency to keep explanations light... Which can mean I leave out a bunch of critical context or logical steps.

@grumpybozo@toad.social
2025-12-08 16:20:57

Or one could use LibreOffice or Apache OpenOffice and not be dependent on some distant service provider.
Online office suites confuse me. It’s unclear what *modern* problem they address. Sharing files is a solved problem. Common data formats exist. mastodon.social/@DevOpsPink/11

Tatiana Mikhaleva (@DevOpsPink@mastodon.social)
Attached: 1 image Proton rolled out Proton Sheets - a spreadsheet Google can’t peek into. Gemini: “Show me your data?” You: “No.” Sheets: also no, but in Swiss.🇨🇭🔐 End-to-end encryption, zero-knowledge, even file names get the Swiss-bank treatment. You open a spreadsheet - Big Tech immediately cries. Somewhere in California, an AI whispers: “But… my training data…” Privacy 1 : 0 AI https://proton.me/blog/sheets-proton-drive #Proton #Privacy #Encryption #CyberSe…

@arXiv_csAI_bot@mastoxiv.page
2025-10-10 10:32:09

Measuring What Matters: The AI Pluralism Index
Rashid Mushkani
arxiv.org/abs/2510.08193 arxiv.org/pdf/2510.08193

Measuring What Matters: The AI Pluralism Index
Artificial intelligence systems increasingly mediate knowledge, communication, and decision making. Development and governance remain concentrated within a small set of firms and states, raising concerns that technologies may encode narrow interests and limit public agency. Capability benchmarks for language, vision, and coding are common, yet public, auditable measures of pluralistic governance are rare. We define AI pluralism as the degree to which affected stakeholders can shape objectives, …

@arXiv_csRO_bot@mastoxiv.page
2025-10-10 09:44:29

GM3: A General Physical Model for Micro-Mobility Vehicles
Grace Cai, Nithin Parepally, Laura Zheng, Ming C. Lin
arxiv.org/abs/2510.07807 ar…

GM3: A General Physical Model for Micro-Mobility Vehicles
Modeling the dynamics of micro-mobility vehicles (MMV) is becoming increasingly important for training autonomous vehicle systems and building urban traffic simulations. However, mainstream tools rely on variants of the Kinematic Bicycle Model (KBM) or mode-specific physics that miss tire slip, load transfer, and rider/vehicle lean. To our knowledge, no unified, physics-based model captures these dynamics across the full range of common MMVs and wheel layouts. We propose the "Generalized Micro-…

@deabigt@universeodon.com
2025-10-04 23:26:37

When Everyone Knows That Everyone Knows...: Common Knowledge and the Mysteries of Money, Power, and Everyday Life goodreads.com/review/show/7893

@primonatura@mstdn.social
2025-11-26 15:00:43

"Why are Amazonian trees getting ‘fatter’?"
#Amazon #Trees #Environment

Why are Amazonian trees getting ‘fatter’?
How have the trees in Amazonia reacted to the rise in CO2 emissions in recent centuries? It is common knowledge that, of all greenhouse gases, CO2 is the most responsible for global warming. The most recent report released by the World Meteorological Organization (WMO) showed that the concentration of carbon in Earth’s atmosphere rose more […]

@arXiv_statML_bot@mastoxiv.page
2025-10-07 10:10:22

Gini-based Model Monitoring: A General Framework with an Application to Non-life Insurance Pricing
Alexej Brauer, Paul Menzel
arxiv.org/abs/2510.04556

Gini-based Model Monitoring: A General Framework with an Application to Non-life Insurance Pricing
In a dynamic landscape where portfolios and environments evolve, maintaining the accuracy of pricing models is critical. To the best of our knowledge, this is the first study to systematically examine concept drift in non-life insurance pricing. We (i) provide an overview of the relevant literature and commonly used methodologies, clarify the distinction between virtual drift and concept drift, and explain their implications for long-run model performance; (ii) review and formalize common perfo…

@arXiv_csCV_bot@mastoxiv.page
2025-09-29 11:15:27

Integrating Background Knowledge in Medical Semantic Segmentation with Logic Tensor Networks
Luca Bergamin, Giovanna Maria Dimitri, Fabio Aiolli
arxiv.org/abs/2509.22399

Integrating Background Knowledge in Medical Semantic Segmentation with Logic Tensor Networks
Semantic segmentation is a fundamental task in medical image analysis, aiding medical decision-making by helping radiologists distinguish objects in an image. Research in this field has been driven by deep learning applications, which have the potential to scale these systems even in the presence of noise and artifacts. However, these systems are not yet perfected. We argue that performance can be improved by incorporating common medical knowledge into the segmentation model's loss function. To…

@arXiv_csLG_bot@mastoxiv.page
2025-09-29 11:35:27

OFMU: Optimization-Driven Framework for Machine Unlearning
Sadia Asif, Mohammad Mohammadi Amiri
arxiv.org/abs/2509.22483 arxiv.org/pdf/2509…

OFMU: Optimization-Driven Framework for Machine Unlearning
Large language models deployed in sensitive applications increasingly require the ability to unlearn specific knowledge, such as user requests, copyrighted materials, or outdated information, without retraining from scratch to ensure regulatory compliance, user privacy, and safety. This task, known as machine unlearning, aims to remove the influence of targeted data (forgetting) while maintaining performance on the remaining data (retention). A common approach is to formulate this as a multi-ob…

@arXiv_csCL_bot@mastoxiv.page
2025-10-02 10:39:31

Exposing the Cracks: Vulnerabilities of Retrieval-Augmented LLM-based Machine Translation
Yanming Sun, Runzhe Zhan, Chi Seng Cheang, Han Wu, Xuebo Liu, Yuyao Niu, Fengying Ye, Kaixin Lan, Lidia S. Chao, Derek F. Wong
arxiv.org/abs/2510.00829

Exposing the Cracks: Vulnerabilities of Retrieval-Augmented LLM-based Machine Translation
\textbf{RE}trieval-\textbf{A}ugmented \textbf{L}LM-based \textbf{M}achine \textbf{T}ranslation (REAL-MT) shows promise for knowledge-intensive tasks like idiomatic translation, but its reliability under noisy retrieval contexts remains poorly understood despite this being a common challenge in real-world deployment. To address this gap, we propose a noise synthesis framework and new metrics to evaluate the robustness of REAL-MT systematically. Using this framework, we instantiate REAL-MT with Q…

@arXiv_csCL_bot@mastoxiv.page
2025-09-26 10:12:41

Who's Laughing Now? An Overview of Computational Humour Generation and Explanation
Tyler Loakman, William Thorne, Chenghua Lin
arxiv.org/abs/2509.21175

Who's Laughing Now? An Overview of Computational Humour Generation and Explanation
The creation and perception of humour is a fundamental human trait, positioning its computational understanding as one of the most challenging tasks in natural language processing (NLP). As an abstract, creative, and frequently context-dependent construct, humour requires extensive reasoning to understand and create, making it a pertinent task for assessing the common-sense knowledge and reasoning abilities of modern large language models (LLMs). In this work, we survey the landscape of computa…