arXiv:2603.22291v1 Announce Type: new Abstract: As Large Language Models (LLMs) become integrated into daily life, they are increasingly used for personal queries, including Sexual and Reproductive Health (SRH), allowing users to chat anonymously without fear of judgment. However, current evaluation methods primarily focus on accuracy, often for objective queries in high-resource languages, and lack criteria to assess usability and safety, especially for low-resource languages and culturally sensitive domains like SRH. This paper introduces LLM Evaluation Framework (LEAF), that […]

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arXiv:2601.02427v1 Announce Type: new Abstract: We introduce NitroGen, a vision-action foundation model for generalist gaming agents that is trained on 40,000 hours of gameplay videos across more than 1,000 games. We incorporate three key ingredients: 1) an internet-scale video-action dataset constructed by automatically extracting player actions from publicly available gameplay videos, 2) a multi-game benchmark environment that can measure cross-game generalization, and 3) a unified vision-action model trained with large-scale behavior cloning. NitroGen exhibits strong competence across diverse […]

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Pepeto just hit another milestone today, with the presale now above $7.43 million raised and all three ecosystem products entering final stages of completion while the rest of the crypto market is still processing the damage from the worst crash in months. Solana dropped thirty one percent in February alone and the Solana price prediction for March looks increasingly fragile, with technical patterns pointing toward further downside if key support levels fail to hold. But in the middle […]

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The Traveling Salesman Problem (TSP) is one of the most famous problems in combinatorial optimization. Given a set of cities and the distances between them, the task is to find the shortest possible route that visits each city exactly once and returns to the starting point. Despite its simple formulation, TSP is NP-hard,and understanding how algorithms search for optimal solutions can be difficult for students encountering the problem for the first time. To make this process more tangible, […]

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arXiv:2603.28965v1 Announce Type: new Abstract: This work presents a hybrid physics-informed and data-driven modeling framework for predictive control of autonomous off-road vehicles operating on deformable terrain. Traditional high-fidelity terramechanics models are often too computationally demanding to be directly used in control design. Modern Koopman operator methods can be used to represent the complex terramechanics and vehicle dynamics in a linear form. We develop a framework whereby a Koopman linear system can be constructed using data from simulations of […]

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Artificial intelligence is moving beyond software and further into the physical side of business. Companies in food production and logistics are starting to use data systems to support day-to-day decisions, not long-term planning. That change is visible in The Hershey Company’s latest strategy update. At its Investor Day, the company said it plans to use AI in its operations, from sourcing analytics to plant automation and fulfilment, with a focus on how the business runs behind the scenes. […]

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To get a first hand understanding of the impact of AI on the software development lifecycle (SDLC), I decided to run an experiment. I wanted to try and write a reasonably complex system from scratch using AI. I didn’t want a “Hello World” or another “To Do” app; I wanted something realistic, something that could be used at scale like we’d build in the enterprise world. The result is Under The Hedge—a fun project blending my passion for […]

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Today, we’re excited to announce that Amazon SageMaker AI MLflow Apps now support MLflow version 3.10, bringing enhanced capabilities for generative AI development and streamlined experiment tracking to your generative AI workflows. Building on the foundations established with Amazon SageMaker AI MLflow Apps, this latest version introduces powerful new features for observability, evaluation, and generative AI development that help data scientists and ML engineers accelerate their AI initiatives from experimentation to production. In this post, we’ll explore what’s […]

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Machine learning models are widely regarded as a way forward to tackle multi-query challenges that arise once expensive black-box simulations such as computational fluid dynamics are investigated. However, ensuring the desired level of accuracy for a certain task at minimal computational cost, e.g. as few black-box samples as possible, remains a challenges. Active learning strategies are used for scalar quantities to overcome this challenges and different so-called infill criteria exists and are commonly employed in several scenarios. Even […]

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