Tootfinder

Understanding the Role of Large Language Models in Competitive Programming
Dongyijie Primo Pan, Ji Zhu, Lan Luo, Zhiqi Gao, Xin Tong, Pan Hui
https://arxiv.org/abs/2509.15867 ht…

Understanding the Role of Large Language Models in Competitive Programming
This paper investigates how large language models (LLMs) are reshaping competitive programming. The field functions as an intellectual contest within computer science education and is marked by rapid iteration, real-time feedback, transparent solutions, and strict integrity norms. Prior work has evaluated LLMs performance on contest problems, but little is known about how human stakeholders -- contestants, problem setters, coaches, and platform stewards -- are adapting their workflows and conte…

Sources: Nvidia's China-only RTX 6000D receives lukewarm demand, with some seeing it as expensive given its performance lags the RTX 5090 (Reuters)
https://www.thestandard.com.hk/tech-and-st

Nvidia's new RTX6000D chip for China finds little favour with major firms, sources say
Nvidia's RTX6000D, its newest artificial intelligence chip tailored for the Chinese market, has seen only lukewarm demand with some major tech firms opting not to place orders, two people with knowledge of procurement discussions said.

VCBench: Benchmarking LLMs in Venture Capital
Rick Chen, Joseph Ternasky, Afriyie Samuel Kwesi, Ben Griffin, Aaron Ontoyin Yin, Zakari Salifu, Kelvin Amoaba, Xianling Mu, Fuat Alican, Yigit Ihlamur
https://arxiv.org/abs/2509.14448

VCBench: Benchmarking LLMs in Venture Capital
Benchmarks such as SWE-bench and ARC-AGI demonstrate how shared datasets accelerate progress toward artificial general intelligence (AGI). We introduce VCBench, the first benchmark for predicting founder success in venture capital (VC), a domain where signals are sparse, outcomes are uncertain, and even top investors perform modestly. At inception, the market index achieves a precision of 1.9%. Y Combinator outperforms the index by a factor of 1.7x, while tier-1 firms are 2.9x better. VCBench p…

Intelligent Vacuum Thermoforming Process
Andi Kuswoyo, Christos Margadji, Sebastian W. Pattinson
https://arxiv.org/abs/2509.13250 https://arxiv.org/pdf/250…

Intelligent Vacuum Thermoforming Process
Ensuring consistent quality in vacuum thermoforming presents challenges due to variations in material properties and tooling configurations. This research introduces a vision-based quality control system to predict and optimise process parameters, thereby enhancing part quality with minimal data requirements. A comprehensive dataset was developed using visual data from vacuum-formed samples subjected to various process parameters, supplemented by image augmentation techniques to improve model t…

Adaptive and robust smartphone-based step detection in multiple sclerosis
Lorenza Angelini, Dimitar Stanev, Marta P{\l}onka, Rafa{\l} Klimas, Natan Napi\'orkowski, Gabriela Gonz\'alez Chan, Lisa Bunn, Paul S Glazier, Richard Hosking, Jenny Freeman, Jeremy Hobart, Jonathan Marsden, Licinio Craveiro, Mike D Rinderknecht, Mattia Zanon
https://

Adaptive and robust smartphone-based step detection in multiple sclerosis
Background: Many attempts to validate gait pipelines that process sensor data to detect gait events have focused on the detection of initial contacts only in supervised settings using a single sensor. Objective: To evaluate the performance of a gait pipeline in detecting initial/final contacts using a step detection algorithm adaptive to different test settings, smartphone wear locations, and gait impairment levels. Methods: In GaitLab (ISRCTN15993728), healthy controls (HC) and people with mul…

27. 28.10.2025 #DCIFJahrestagung in #Darmstadt

Themen:
Data Sourcing & Quality – verlässliche Information in der Datenflut

Intellectual Property & Value Creation – Patentwissen strategisch nutzen
Future-Oriented CI – Foresight & KI für…

Autonomous Reporting of Normal Chest X-rays by Artificial Intelligence in the United Kingdom. Can We Take the Human Out of the Loop?
Katrina Nash, James Vaz, Ahmed Maiter, Christopher Johns, Nicholas Woznitza, Aditya Kale, Abdala Espinosa Morgado, Rhidian Bramley, Mark Hall, David Lowe, Alex Novak, Sarim Ather
https://arxiv.org/abs/2509.13…

Autonomous Reporting of Normal Chest X-rays by Artificial Intelligence in the United Kingdom. Can We Take the Human Out of the Loop?
Chest X-rays (CXRs) are the most commonly performed imaging investigation. In the UK, many centres experience reporting delays due to radiologist workforce shortages. Artificial intelligence (AI) tools capable of distinguishing normal from abnormal CXRs have emerged as a potential solution. If normal CXRs could be safely identified and reported without human input, a substantial portion of radiology workload could be reduced. This article examines the feasibility and implications of autonomou…

Another demonstration that we MUST differentiate between the ability to reproduce some kind of data and the ability to perform abstract reasoning.
So-called “artificial intelligence” tools are just stochastic parrots.
Beware the marketing hype.
https://

Towards Effective Prompt Stealing Attack against Text-to-Image Diffusion Models
Shiqian Zhao, Chong Wang, Yiming Li, Yihao Huang, Wenjie Qu, Siew-Kei Lam, Yi Xie, Kangjie Chen, Jie Zhang, Tianwei Zhang
https://arxiv.org/abs/2508.06837

Towards Effective Prompt Stealing Attack against Text-to-Image Diffusion Models
Text-to-Image (T2I) models, represented by DALL$\cdot$E and Midjourney, have gained huge popularity for creating realistic images. The quality of these images relies on the carefully engineered prompts, which have become valuable intellectual property. While skilled prompters showcase their AI-generated art on markets to attract buyers, this business incidentally exposes them to \textit{prompt stealing attacks}. Existing state-of-the-art attack techniques reconstruct the prompts from a fixed se…

The MeerKAT Galaxy Cluster Legacy Survey - II. Catalogue of the diffuse radio emission in MeerKAT-GCLS clusters
Konstantinos Kolokythas, Tiziana Venturi, Kenda Knowles, Marcus Br\"uggen, Francesco de Gasperin, S. Precious Sikhosana, Tracy E. Clarke, Oleg Smirnov, S. Ilani Loubser, Kavilian Moodley
https://arxiv.org/abs/2509.05442

The MeerKAT Galaxy Cluster Legacy Survey - II. Catalogue of the diffuse radio emission in MeerKAT-GCLS clusters
We present a follow-up study focused on cluster-scale diffuse radio emissions in 115 galaxy clusters in the Southern sky, using full-resolution (7.8") and tapered low-resolution (15") images from the MeerKAT Galaxy Cluster Legacy Survey (MGCLS). In this MGCLS follow-up paper, we update and quantitatively characterise the presence of diffuse radio emission and provide detailed catalogue information on its radio properties at 1.28 GHz. As the MGCLS sample is heterogeneous and was initially used a…