Tootfinder

Understanding the Error Sensitivity of Privacy-Aware Computing
Mat\'ias Mazzanti (University of Buenos Aires), Esteban Mocskos (University of Buenos Aires), Augusto Vega (IBM T. J. Watson Research Center), Pradip Bose (IBM T. J. Watson Research Center)
https://arxiv.org/abs/2506.07957

Understanding the Error Sensitivity of Privacy-Aware Computing
Homomorphic Encryption (HE) enables secure computation on encrypted data without decryption, allowing a great opportunity for privacy-preserving computation. In particular, domains such as healthcare, finance, and government, where data privacy and security are of utmost importance, can benefit from HE by enabling third-party computation and services on sensitive data. In other words, HE constitutes the "Holy Grail" of cryptography: data remains encrypted all the time, being protected while in …

Cyclic Equalizability of Words and Its Application to Card-Based Cryptography
Kazumasa Shinagawa, Koji Nuida
https://arxiv.org/abs/2507.04916 https://

Cyclic Equalizability of Words and Its Application to Card-Based Cryptography
Card-based cryptography is a research area to implement cryptographic procedures using a deck of physical cards. In recent years, it has been found to be related to finite group theory and algebraic combinatorics, and is becoming more and more closely connected to the field of mathematics. In this paper, we discuss the relationship between card-based cryptography and combinatorics on words for the first time. In particular, we focus on cyclic equality of words. We say that a set of words are cy…

USC professor Allison Marsh writes this delightful short article for IEEE Spectrum about Marvin Minsky and Seymour Papert's British counterparts in Cambridge and how, in their case, a document (the Lighthill Report) precipitated cuts in British AI research funding in ways similar to how funding was temporarily cut in the U.S. following MIT's publishing of Minsky and Papert's "Perceptrons" in 1969.
"Freddy the Robot Was the Fall Guy for British AI"

Freddy the Robot Was the Fall Guy for British AI

Its creator lost a power struggle that led to an AI winter in the 1970s

Building on the 90s, statistical n-gram language models, trained on vast text collections, became the backbone of NLP research. They fueled advancements in nearly all NLP techniques of the era, laying the groundwork for today's AI.
F. Jelinek (1997), Statistical Methods for Speech Recognition, MIT Press, Cambridge, MA
#NLP

An analysis of 15M biomedical abstracts from 2010 to 2024 finds researchers using AI to write abstracts use certain words far more often than those who don't (Gina Kolata/New York Times)
https://www.nytimes.com/2025/…

454 Hints That a Chatbot Wrote Part of a Biomedical Researcher’s Paper
Scientists show that the frequency of a set of words seems to have increased in published study abstracts since ChatGPT was released into the world.

This https://arxiv.org/abs/2504.21398 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

In a Few Words: Comparing Weak Supervision and LLMs for Short Query Intent Classification
User intent classification is an important task in information retrieval. Previously, user intents were classified manually and automatically; the latter helped to avoid hand labelling of large datasets. Recent studies explored whether LLMs can reliably determine user intent. However, researchers have recognized the limitations of using generative LLMs for classification tasks. In this study, we empirically compare user intent classification into informational, navigational, and transactional c…

Researchers Jailbreak AI by Flooding It With Bullshit Jargon https://www.404media.co/researchers-jailbreak-ai-by-flooding-it-with-bullshit-jargon/

New around here, hi!
For those who'd like a big old dose of "yes we can" energy,
please check out
"Words to Win By "
where every episode details a campaign we've won somewhere
and delves into the research, messaging & strategies used to do it.
https://wordstowinby-pod.com/

Words to Win By
Words to Win By, formerly Brave New Words, takes listeners on a journey around the globe with renowned communications researcher and campaign advisor Anat Shenker-Osorio as she unpacks real-world narrative shifts that led to real-world victories.

GloBIAS: strengthening the foundations of BioImage Analysis
A. A. Corbat (BioImage Informatics Unit, Science for Life Laboratory and Department of Information Technology, Uppsala University, Sweden), C. G. Walther (German BioImaging, Gesellschaft f\"ur Mikroskopie und Bildanalyse e.V., Konstanz, Germany, University of Vienna, Vienna, Austria), L. R. de la Ballina (Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Montebe…

GloBIAS: strengthening the foundations of BioImage Analysis
There is a global need for BioImage Analysis (BIA) as advances in life sciences increasingly rely on cutting-edge imaging systems that have dramatically expanded the complexity and dimensionality of biological images. Turning these data into scientific discoveries requires people with effective data management skills and knowledge of state-of-the-art image processing and data analysis, in other words, BioImage Analysts. The Global BioImage Analysts' Society (GloBIAS) aims to enhance the profile…

AI-Based Reconstruction from Inherited Personal Data: Analysis, Feasibility, and Prospects
Mark Zilberman
https://arxiv.org/abs/2507.03059 https://

AI-Based Reconstruction from Inherited Personal Data: Analysis, Feasibility, and Prospects
This article explores the feasibility of creating an "electronic copy" of a deceased researcher by training artificial intelligence (AI) on the data stored in their personal computers. By analyzing typical data volumes on inherited researcher computers, including textual files such as articles, emails, and drafts, it is estimated that approximately one million words are available for AI training. This volume is sufficient for fine-tuning advanced pre-trained models like GPT-4 to replicate a res…