Tootfinder

AI doesn’t learn like we do. GoPro'd toddlers see mostly knees—but they can ID a dog after a few glimpses, while LLMs need billions of examples. Neuroscience suggests AI intelligence is gathered very differently than ours https://www.linkedin.com/p…

We in Game Workers Unite Ireland stand in solidarity with Animation Workers of Ireland, and the international trade union coalition happening to organise against the threat of AI in the animation industry, and we support their call to acton.
Join them Thursday 12 June at 14:00 at the Pâquier in Annecy!!
#Animation

Die re:publica hat dem Boomer Stefan emotional und inhaltlich eine Menge gebracht. Sie hat mir Mut gemacht, da sich viele junge Menschen engagieren. Doch natürlich sind da auch Fragen und Sorgen. Der besonders persönliche Teil 3 meiner #rp25-Impressionen.

Nicht nur Generation XYZ auf der re:publica 25: Zwischen Boomer-Nostalgie, Jugendpower und persönlichen Treffen
Die re:publica hat dem Boomer Stefan emotional und inhaltlich eine Menge gebracht. Sie hat mir Mut gemacht, da sich viele junge Menschen engagieren. Doch natürlich sind da auch Fragen und Sorgen. D…

Semantics-Guided Generative Image Compression
Cheng-Lin Wu, Hyomin Choi, Ivan V. Baji\'c
https://arxiv.org/abs/2505.24015 https://

Semantics-Guided Generative Image Compression
Advancements in text-to-image generative AI with large multimodal models are spreading into the field of image compression, creating high-quality representation of images at extremely low bit rates. This work introduces novel components to the existing multimodal image semantic compression (MISC) approach, enhancing the quality of the generated images in terms of PSNR and perceptual metrics. The new components include semantic segmentation guidance for the generative decoder, as well as content…

Next generation captchas will be like: »mark all texts that are not AI generated«

This https://arxiv.org/abs/2502.11844 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

BaxBench: Can LLMs Generate Correct and Secure Backends?
Automatic program generation has long been a fundamental challenge in computer science. Recent benchmarks have shown that large language models (LLMs) can effectively generate code at the function level, make code edits, and solve algorithmic coding tasks. However, to achieve full automation, LLMs should be able to generate production-quality, self-contained application modules. To evaluate the capabilities of LLMs in solving this challenge, we introduce BaxBench, a novel evaluation benchmark c…

A generating set of Reidemeister moves of oriented virtual knots
Danish Ali
https://arxiv.org/abs/2505.24094 https://arxiv.org/pdf/25…

A generating set of Reidemeister moves of oriented virtual knots
In oriented knot theory, verifying a quantity is an invariant involves checking its invariance under all oriented Reidemeister moves, a process that can be intricate and time-consuming. A generating set of oriented moves simplifies this by requiring verification for only a minimal subset from which all other moves can be derived. While generating sets for classical oriented Reidemeister moves are well-established, their virtual counterparts are less explored. In this study, we enumerate the ori…

Robust Distribution Network Reconfiguration Using Mapping-based Column-and-Constraint Generation
Runjie Zhang, Kaiping Qu, Changhong Zhao, Wanjun Huang
https://arxiv.org/abs/2505.24677

Robust Distribution Network Reconfiguration Using Mapping-based Column-and-Constraint Generation
The integration of intermittent renewable energy sources into distribution networks introduces significant uncertainties and fluctuations, challenging their operational security, stability, and efficiency. This paper considers robust distribution network reconfiguration (RDNR) with renewable generator resizing, modeled as a two-stage robust optimization (RO) problem with decision-dependent uncertainty (DDU). Our model optimizes resizing decisions as the upper bounds of renewable generator outpu…

Enhancing Critical Thinking in Generative AI Search with Metacognitive Prompts
Anjali Singh, Zhitong Guan, Soo Young Rieh
https://arxiv.org/abs/2505.24014 …

Enhancing Critical Thinking in Generative AI Search with Metacognitive Prompts
The growing use of Generative AI (GenAI) conversational search tools has raised concerns about their effects on people's metacognitive engagement, critical thinking, and learning. As people increasingly rely on GenAI to perform tasks such as analyzing and applying information, they may become less actively engaged in thinking and learning. This study examines whether metacognitive prompts - designed to encourage people to pause, reflect, assess their understanding, and consider multiple perspec…

A Reward-driven Automated Webshell Malicious-code Generator for Red-teaming
Yizhong Ding
https://arxiv.org/abs/2505.24252 https://arx…

A Reward-driven Automated Webshell Malicious-code Generator for Red-teaming
Frequent cyber-attacks have elevated WebShell exploitation and defense to a critical research focus within network security. However, there remains a significant shortage of publicly available, well-categorized malicious-code datasets organized by obfuscation method. Existing malicious-code generation methods, which primarily rely on prompt engineering, often suffer from limited diversity and high redundancy in the payloads they produce. To address these limitations, we propose \textbf{RAWG}, a…