Tootfinder

🇺🇦 #NowPlaying on KEXP's #MiddayShow
Samantha Crain:
🎵 Ridin’ Out The Storm
#SamanthaCrain
https://samanthacrain.bandcamp.com/track/ridin-out-the-storm
https://open.spotify.com/track/3in5CVZj0MDdf0Q88nZ24V

Announcing sff: A fast, on-the-fly SemanticFileFinder written in Rust! 🦀
It scans a directory (like your notes or a repo), finds the most semantically relevant text chunks for your query, and lets you open the file in a text editor of your choice.
No vector DBs, no GPU needed. Indexes ~2500 files with 10k chunks in 250ms on a CPU.
Perfect for searching Obsidian vaults, codebases, and more.
𝚌𝚊𝚛𝚐𝚘 𝚒𝚗𝚜𝚝𝚊𝚕𝚕 𝚜𝚏𝚏
𝚜𝚏𝚏 "𝚠𝚘𝚛𝚔𝚒𝚗𝚐 𝚠𝚒𝚝𝚑 𝚐𝚒𝚝"

GitHub - do-me/sff: CLI for semantic search on your computer. Searches text files and identifies the most relevant chunks to your query.
CLI for semantic search on your computer. Searches text files and identifies the most relevant chunks to your query. - GitHub - do-me/sff: CLI for semantic search on your computer. Searches text f...

Stacked Intelligent Metasurfaces for Multi-Modal Semantic Communications
Guojun Huang, Jiancheng An, Lu Gan, Dusit Niyato, M\'erouane Debbah, Tie Jun Cui
https://arxiv.org/abs/2506.12368

Stacked Intelligent Metasurfaces for Multi-Modal Semantic Communications
Semantic communication (SemCom) powered by generative artificial intelligence enables highly efficient and reliable information transmission. However, it still necessitates the transmission of substantial amounts of data when dealing with complex scene information. In contrast, the stacked intelligent metasurface (SIM), leveraging wave-domain computing, provides a cost-effective solution for directly imaging complex scenes. Building on this concept, we propose an innovative SIM-aided multi-moda…

SemanticST: Spatially Informed Semantic Graph Learning for1 Clustering, Integration, and Scalable Analysis of Spatial2 Transcriptomics
Roxana Zahedi, Ahmadreza Argha, Nona Farbehi, Ivan Bakhshayeshi, Youqiong Ye, Nigel H. Lovell, Hamid Alinejad-Rokny
https://arxiv.org/abs/2506.11491

SemanticST: Spatially Informed Semantic Graph Learning for1 Clustering, Integration, and Scalable Analysis of Spatial2 Transcriptomics
Spatial transcriptomics (ST) technologies enable gene expression profiling with spatial resolution, offering unprecedented insights into tissue organization and disease heterogeneity. However, current analysis methods often struggle with noisy data, limited scalability, and inadequate modelling of complex cellular relationships. We present SemanticST, a biologically informed, graph-based deep learning framework that models diverse cellular contexts through multi-semantic graph construction. Sem…

Semantic Communications in 6G: Coexistence, Multiple Access, and Satellite Networks
Ishtiaque Ahmed, Yingzhuo Sun, Jingwen Fu, Alper Kose, Leila Musavian, Ming Xiao, Berna Ozbek
https://arxiv.org/abs/2506.11779

Semantic Communications in 6G: Coexistence, Multiple Access, and Satellite Networks
The exponential growth of wireless users and bandwidth constraints necessitates innovative communication paradigms for next-generation networks. Semantic Communication (SemCom) emerges as a promising solution by transmitting extracted meaning rather than raw bits, enhancing spectral efficiency and enabling intelligent resource allocation. This paper explores the integration of SemCom with conventional Bit-based Communication (BitCom) in heterogeneous networks, highlighting key challenges and op…

Beyond Formal Semantics for Capabilities and Skills: Model Context Protocol in Manufacturing
Luis Miguel Vieira da Silva, Aljosha K\"ocher, Felix Gehlhoff
https://arxiv.org/abs/2506.11180

Beyond Formal Semantics for Capabilities and Skills: Model Context Protocol in Manufacturing
Explicit modeling of capabilities and skills -- whether based on ontologies, Asset Administration Shells, or other technologies -- requires considerable manual effort and often results in representations that are not easily accessible to Large Language Models (LLMs). In this work-in-progress paper, we present an alternative approach based on the recently introduced Model Context Protocol (MCP). MCP allows systems to expose functionality through a standardized interface that is directly consumab…

Alphabet Index Mapping: Jailbreaking LLMs through Semantic Dissimilarity
Bilal Saleh Husain
https://arxiv.org/abs/2506.12685 https://…

Alphabet Index Mapping: Jailbreaking LLMs through Semantic Dissimilarity
Large Language Models (LLMs) have demonstrated remarkable capabilities, yet their susceptibility to adversarial attacks, particularly jailbreaking, poses significant safety and ethical concerns. While numerous jailbreak methods exist, many suffer from computational expense, high token usage, or complex decoding schemes. Liu et al. (2024) introduced FlipAttack, a black-box method that achieves high attack success rates (ASR) through simple prompt manipulation. This paper investigates the underly…

Und hier haben wir es: eine logisch-semantische Injektion: unmarkierte Modifikationen der Funktionsweise von LLMs, die unser Denken nudgen und damit unsere logisch-semantische Souveränität untergraben: https://toot.cafe/@baldur/113934035009657696
Hintergrund:

Vice Media hires ex-NBCUniversal executive Adam Stotsky as CEO, aiming to build up its studio and advertising arms with a focus on "provocative storytelling" (Isabella Simonetti/Wall Street Journal)
https://www.wsj.com/business/m…

LeanExplore: A search engine for Lean 4 declarations
Justin Asher (Independent Researcher)
https://arxiv.org/abs/2506.11085 https://a…

LeanExplore: A search engine for Lean 4 declarations
The expanding Lean 4 ecosystem poses challenges for navigating its vast libraries. This paper introduces LeanExplore, a search engine for Lean 4 declarations. LeanExplore enables users to semantically search for statements, both formally and informally, across select Lean 4 packages (including Batteries, Init, Lean, Mathlib, PhysLean, and Std). This search capability is powered by a hybrid ranking strategy, integrating scores from a multi-source semantic embedding model (capturing conceptual me…