Tootfinder

Iran's largest crypto exchange Nobitex says it was hacked, and pro-Israel group Predatory Sparrow claims responsibility; Elliptic: $90M was stolen and "burned" (Zack Whittaker/TechCrunch)
https://techcrunch.com/2025/06/18/hack

Hackers steal and destroy millions from Iran's largest crypto exchange | TechCrunch
It's the latest cyberattack on Iran claimed by a pro-Israeli hacking group since the latest flare up in tensions between the two countries.

Trump cuts to foreign aid leave food destined for desperate millions rotting in storage. »The dismantling of USAID and cuts to humanitarian aid has been devastating and unacceptable,« said one international aid group. https://www.commondreams.org/news/trump-usa…

lkml_thread: Linux kernel mailing list
A bipartite network of contributions by users to threads on the Linux kernel mailing list. A left node is a person, and a right node is a thread, and each timestamped edge (i,j,t) denotes that user i contributed to thread j at time t. The date of the snapshot is not given.
This network has 379554 nodes and 1565683 edges.
Tags: Social, Communication, Unweighted, Timestamps

DPRK supplies Russia with millions of shells: the alliance of dictators grows stronger: https://benborges.xyz/2025/07/17/dprk-supplies-russia-with-millions.html

Exploring MLLMs Perception of Network Visualization Principles
Jacob Miller, Markus Wallinger, Ludwig Felder, Timo Brand, Henry F\"orster, Johannes Zink, Chunyang Chen, Stephen Kobourov
https://arxiv.org/abs/2506.14611

Exploring MLLMs Perception of Network Visualization Principles
In this paper, we test whether Multimodal Large Language Models (MLLMs) can match human-subject performance in tasks involving the perception of properties in network layouts. Specifically, we replicate a human-subject experiment about perceiving quality (namely stress) in network layouts using GPT-4o and Gemini-2.5. Our experiments show that giving MLLMs exactly the same study information as trained human participants results in a similar performance to human experts and exceeds the performanc…

Meditation Suite 2
#MellowMusic #MeditationMusic #NowPlaying

Meditation Suite 2 #NowPlaying
Stan Stewart - @muz4now

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem
Yanxu Mao, Tiehan Cui, Peipei Liu, Datao You, Hongsong Zhu
https://arxiv.org/abs/2506.15170

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem
Large language models (LLMs) are rapidly evolving from single-modal systems to multimodal LLMs and intelligent agents, significantly expanding their capabilities while introducing increasingly severe security risks. This paper presents a systematic survey of the growing complexity of jailbreak attacks and corresponding defense mechanisms within the expanding LLM ecosystem. We first trace the developmental trajectory from LLMs to MLLMs and Agents, highlighting the core security challenges emergi…

Folk at #DH2025 might be interested in this article 'From handwriting to searchable text: using AI to make millions of historical documents accessible'

From handwriting to searchable text: using AI to make millions of historical documents accessible
In April 2025 the Swedish National Archives made 1,2 million digital images of archival documents into searchable, machine readable text — making the information in the archives more accessible than…

Vela: Scalable Embeddings with Voice Large Language Models for Multimodal Retrieval
Ruofan Hu, Yan Xia, Minjie Hong, Jieming Zhu, Bo Chen, Xiaoda Yang, Minghui Fang, Tao Jin
https://arxiv.org/abs/2506.14445

Vela: Scalable Embeddings with Voice Large Language Models for Multimodal Retrieval
Multimodal large language models (MLLMs) have seen substantial progress in recent years. However, their ability to represent multimodal information in the acoustic domain remains underexplored. In this work, we introduce Vela, a novel framework designed to adapt MLLMs for the generation of universal multimodal embeddings. By leveraging MLLMs with specially crafted prompts and selected in-context learning examples, Vela effectively bridges the modality gap across various modalities. We then prop…

An Indicator analysis of 85 AI "nudify" websites: the sites averaged 18.5M monthly visitors, may generate up to $36M annually, and rely on Big Tech services (Matt Burgess/Wired)
https://www.wired.com/story/ai-nudify-websites-are-raking-in-millions-…

AI 'Nudify' Websites Are Raking in Millions of Dollars
Millions of people are accessing harmful AI “nudify” websites. New analysis says the sites are making millions and rely on tech from US companies.