Tootfinder

Ok ...
Of ik maar minstens €3000* wil ophoesten, omdat blijkbaar de hele ontstane situatie mijn schuld is.
* Zou dat bedrag zijn , maar al pratend blijkt t al mompelend nog veel hoger re kinnen zijn.
Wil er aan meewerken, maar heb al tijden geleden aangegeven dat t zo niet ging en om hulp gevraagd waar overheen gelopen werd .
Onder protest tekenen kan niet, want het is geen voorstel van ons*: het is iets tussen u en het bedrijf wat we bedacht hebben.
Snap er de…

Well, after having lots of fun and success #VibeCoding my own #Obsidian clone, I finally went back to Obsidian. Having someone else do the work is great :)
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GitHub - DennisFaucher/ToastNotes: A simple, browser-based Markdown note-taking app with a modern UI, built using [Toast UI Editor](https://ui.toast.com/tui-editor), Node.js, and Docker. Notes are saved as Markdown files on the server and can be created, edited, renamed, deleted, printed, or exported.
A simple, browser-based Markdown note-taking app with a modern UI, built using [Toast UI Editor](https://ui.toast.com/tui-editor), Node.js, and Docker. Notes are saved as Markdown files on the serv...

This https://arxiv.org/abs/2505.19887 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Deconstructing Obfuscation: A four-dimensional framework for evaluating Large Language Models assembly code deobfuscation capabilities
Large language models (LLMs) have shown promise in software engineering, yet their effectiveness for binary analysis remains unexplored. We present the first comprehensive evaluation of commercial LLMs for assembly code deobfuscation. Testing seven state-of-the-art models against four obfuscation scenarios (bogus control flow, instruction substitution, control flow flattening, and their combination), we found striking performance variations--from autonomous deobfuscation to complete failure. We…

Mutli-Level Autoencoder: Deep Learning Based Channel Coding and Modulation
Ahmad Abdel-Qader, Anas Chaaban, Mohamed S. Shehata
https://arxiv.org/abs/2506.23511

Mutli-Level Autoencoder: Deep Learning Based Channel Coding and Modulation
In this paper, we design a deep learning-based convolutional autoencoder for channel coding and modulation. The objective is to develop an adaptive scheme capable of operating at various signal-to-noise ratios (SNR)s without the need for re-training. Additionally, the proposed framework allows validation by testing all possible codes in the codebook, as opposed to previous AI-based encoder/decoder frameworks which relied on testing only a small subset of the available codes. This limitation in …

This https://arxiv.org/abs/2505.00616 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

Catastrophic Liability: Managing Systemic Risks in Frontier AI Development
As artificial intelligence systems grow more capable and autonomous, frontier AI development poses potential systemic risks that could affect society at a massive scale. Current practices at many AI labs developing these systems lack sufficient transparency around safety measures, testing procedures, and governance structures. This opacity makes it challenging to verify safety claims or establish appropriate liability when harm occurs. Drawing on liability frameworks from nuclear energy, aviati…