Tootfinder

Q&A with Hugging Face Chief Ethics Scientist Margaret Mitchell on aligning AI development with human needs, the "illusion of consensus" around AGI, and more (Melissa Heikkilä/Financial Times)
https://www.ft.com/content/7089bff2-25fc-4a25-98bf-8828ab24…

Margaret Mitchell: artificial general intelligence is ‘just vibes and snake oil’
One of the pioneers of AI ethics explains why human needs should be the central driver in the development of the technology

Interesting study on perceptions about AI in the general US public and among US AI experts (both from academia and companies).
https://www.pewresearch.org/internet/2025/04/03/how-the-us-public-and-ai-experts-view-arti…

How the U.S. Public and AI Experts View Artificial Intelligence
These groups are far apart in their enthusiasm and predictions for AI, but both want more personal control and worry about too little regulation.

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[1/7]:
A philosophical and ontological perspective on Artificial General Intelligence and the Metaverse

A look at the lack of consensus in the tech industry on what AGI is, whether LLMs are the best path to it, and what AGI might look like if or when it arrives (Melissa Heikkilä/Financial Times)

Why Big Tech cannot agree on artificial general intelligence
It has been tipped as the next big breakthrough out of Silicon Valley, but is it a scientific goal — or a marketing buzzword?

Evaluating Large Language Models for Phishing Detection, Self-Consistency, Faithfulness, and Explainability
Shova Kuikel, Aritran Piplai, Palvi Aggarwal
https://arxiv.org/abs/2506.13746

Evaluating Large Language Models for Phishing Detection, Self-Consistency, Faithfulness, and Explainability
Phishing attacks remain one of the most prevalent and persistent cybersecurity threat with attackers continuously evolving and intensifying tactics to evade the general detection system. Despite significant advances in artificial intelligence and machine learning, faithfully reproducing the interpretable reasoning with classification and explainability that underpin phishing judgments remains challenging. Due to recent advancement in Natural Language Processing, Large Language Models (LLMs) sho…

Cada vez que veo noticias sobre las IAs como esta pienso que aquí nos enteramos de estas miserias, se comparten, se comentan... pero ¿y fuera? Por ejemplo, la gente en general es consciente de lo que supone para su privacidad que una IA grabe y "transcriba" una conversación confidencial con su médico?

Bridging the Artificial Intelligence Governance Gap: The United States' and China's Divergent Approaches to Governing General-Purpose Artificial Intelligence
Oliver Guest, Kevin Wei
https://arxiv.org/abs/2506.03497

Bridging the Artificial Intelligence Governance Gap: The United States' and China's Divergent Approaches to Governing General-Purpose Artificial Intelligence
The United States and China are among the world's top players in the development of advanced artificial intelligence (AI) systems, and both are keen to lead in global AI governance and development. A look at U.S. and Chinese policy landscapes reveals differences in how the two countries approach the governance of general-purpose artificial intelligence (GPAI) systems. Three areas of divergence are notable for policymakers: the focus of domestic AI regulation, key principles of domestic AI regul…

Evaluating Large Language Models for Phishing Detection, Self-Consistency, Faithfulness, and Explainability
Shova Kuikel, Aritran Piplai, Palvi Aggarwal
https://arxiv.org/abs/2506.13746

Evaluating Large Language Models for Phishing Detection, Self-Consistency, Faithfulness, and Explainability
Phishing attacks remain one of the most prevalent and persistent cybersecurity threat with attackers continuously evolving and intensifying tactics to evade the general detection system. Despite significant advances in artificial intelligence and machine learning, faithfully reproducing the interpretable reasoning with classification and explainability that underpin phishing judgments remains challenging. Due to recent advancement in Natural Language Processing, Large Language Models (LLMs) sho…

Generative Representational Learning of Foundation Models for Recommendation
Zheli Zhou, Chenxu Zhu, Jianghao Lin, Bo Chen, Ruiming Tang, Weinan Zhang, Yong Yu
https://arxiv.org/abs/2506.11999

Generative Representational Learning of Foundation Models for Recommendation
Developing a single foundation model with the capability to excel across diverse tasks has been a long-standing objective in the field of artificial intelligence. As the wave of general-purpose foundation models sweeps across various domains, their influence has significantly extended to the field of recommendation systems. While recent efforts have explored recommendation foundation models for various generative tasks, they often overlook crucial embedding tasks and struggle with the complexit…

Meter, which sells and maintains packages of custom data center networking equipment, raised $170M led by General Catalyst at a $1B valuation (Michael J. de la Merced/New York Times)
https://www.nytimes.com/2025/06/12/business/dealbook/meter-n…

Meter, Networking Start-Up, Raises $170 Million
The company has collected $170 million in new capital as it seeks to help connect data centers and other businesses in the age of artificial intelligence.

I coined a new phrase!
Basilisk puppet (n). A person who relentlessly shills for artificial intelligence. Makes strong claims that general AI is happening any day now or that existing AIs can make everyone more efficient and happier. See also Roko's Basilisk.

Stochastic Moving Anchor Algorithms and a Popov's Scheme with Moving Anchor
James Alcala, Yat Tin Chow, Mahesh Sunkula
https://arxiv.org/abs/2506.07290

Stochastic Moving Anchor Algorithms and a Popov's Scheme with Moving Anchor
Since their introduction, anchoring methods in extragradient-type saddlepoint problems have inspired a flurry of research due to their ability to provide order-optimal rates of accelerated convergence in very general problem settings. Such guarantees are especially important as researchers consider problems in artificial intelligence (AI) and machine learning (ML), where large problem sizes demand immense computational power. Much of the more recent works explore theoretical aspects of this new…

[VIDEO] The Government Knows AGI is Coming | The Ezra Klein Show
#AI

This https://arxiv.org/abs/2505.15173 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

AvatarShield: Visual Reinforcement Learning for Human-Centric Video Forgery Detection
The rapid advancement of Artificial Intelligence Generated Content (AIGC) technologies, particularly in video generation, has led to unprecedented creative capabilities but also increased threats to information integrity, identity security, and public trust. Existing detection methods, while effective in general scenarios, lack robust solutions for human-centric videos, which pose greater risks due to their realism and potential for legal and ethical misuse. Moreover, current detection approach…

This https://arxiv.org/abs/2504.15585 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment
The remarkable success of Large Language Models (LLMs) has illuminated a promising pathway toward achieving Artificial General Intelligence for both academic and industrial communities, owing to their unprecedented performance across various applications. As LLMs continue to gain prominence in both research and commercial domains, their security and safety implications have become a growing concern, not only for researchers and corporations but also for every nation. Currently, existing surveys…

Gauging Growth: AGI Mathematical Metrics for Economic Progress
Davit Gondauri
https://arxiv.org/abs/2506.03156 https://arxiv.org/pdf/…

Gauging Growth: AGI Mathematical Metrics for Economic Progress
Today, the economy is greatly influenced by Artificial General Intelligence (AGI). The purpose of this paper is to determine the impact of the quantitative relations of AGI on the country's economic parameters. The authors use the analysis of historical data in the research, develop a new mathematical algorithm that refers to the level of AGI development, and conduct a regression analysis. The economic effect of AGI is deduced if it affects the growth of real GDP. As a result of the analysis, i…

Evaluating Gemini in an arena for learning
LearnLM Team, Abhinit Modi, Aditya Srikanth Veerubhotla, Aliya Rysbek, Andrea Huber, Ankit Anand, Avishkar Bhoopchand, Brett Wiltshire, Daniel Gillick, Daniel Kasenberg, Eleni Sgouritsa, Gal Elidan, Hengrui Liu, Holger Winnemoeller, Irina Jurenka, James Cohan, Jennifer She, Julia Wilkowski, Kaiz Alarakyia, Kevin R. McKee, Komal Singh, Lisa Wang, Markus Kunesch, Miruna P\^islar, Niv Efron, Parsa Mahmoudieh, Pierre-Alexandre Kamienny, Sara Wiltb…

Evaluating Gemini in an arena for learning
Artificial intelligence (AI) is poised to transform education, but the research community lacks a robust, general benchmark to evaluate AI models for learning. To assess state-of-the-art support for educational use cases, we ran an "arena for learning" where educators and pedagogy experts conduct blind, head-to-head, multi-turn comparisons of leading AI models. In particular, $N = 189$ educators drew from their experience to role-play realistic learning use cases, interacting with two models se…