arXiv:2603.20903v1 Announce Type: cross Abstract: Data unfolding — the removal of noise or artifacts from measurements — is a fundamental task across the experimental sciences. Of particular interest are applications in physics, where the dominant approach is Richardson-Lucy (RL) deconvolution. The classical RL approach aims to find denoised data that, once passed through the noise model, is as close as possible to the measured data in terms of Kullback-Leibler (KL) divergence. This requires that the support of the […]

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Introduction Disclaimer: This article is a cross post from Pytorch Medium Blog Post. One of the most exciting advancements, that has pushed the frontier of the Artificial Intelligence (AI) in recent years, is Deep Reinforcement Learning (DRL). DRL belongs to the family of machine learning algorithms. It assumes that intelligent machines can learn from their actions similar to the way humans learn from experience. Over the recent years we could witness some impressive real-world applications of DRL. The […]

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arXiv:2602.10171v1 Announce Type: new Abstract: As large language models (LLMs) continue to advance in programming tasks, LLM-driven coding systems have evolved from one-shot code generation into complex systems capable of iterative improvement during inference. However, existing code benchmarks primarily emphasize static correctness and implicitly assume fixed model capability during inference. As a result, they do not capture inference-time self-evolution, such as whether accuracy and efficiency improve as an agent iteratively refines its solutions. They also provide limited accounting […]

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arXiv:2603.22289v1 Announce Type: new Abstract: Knowledge Tracing (KT) models students’ evolving knowledge states to predict future performance, serving as a foundation for personalized education. While traditional deep learning models achieve high accuracy, they often lack interpretability. Large Language Models (LLMs) offer strong reasoning capabilities but struggle with limited context windows and hallucinations. Furthermore, existing LLM-based methods typically require expensive fine-tuning, limiting scalability and adaptability to new data. We propose MERIT (Memory-Enhanced Retrieval for Interpretable Knowledge Tracing), a training-free […]

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Hi everybody, I wanted to share a passion project I’ve been working on: ARC-RL! It’s an ARC Raiders-inspired Reinforcement Learning playground where you can train iconic robots to walk. So far, I’ve built the Leaper, the Bastion, and her majesty, the Queen. More is coming very soon! You can check out the code and see them in action here: https://github.com/CarloRomeo427/ARC_RL.git Enjoy! https://reddit.com/link/1snugly/video/xlpx9gcalpvg1/player https://reddit.com/link/1snugly/video/234r4hcalpvg1/player https://reddit.com/link/1snugly/video/uf5k3gcalpvg1/player submitted by /u/ObscureSM [link] [comments]

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Most founders have a version of this story. Personally, I’ve watched this happen (and made this mistake myself): the tool looks great in a demo, then headcount grows and reality hits. You pick a modern, impressive-looking tool. The demo is smooth. The UI feels fast. Everyone’s excited. For a while, it works. Then the company grows. You hire more people. Someone leaves. Finance asks for historical data. An auditor wants proof of approvals. A manager needs limited access. […]

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arXiv:2604.15342v1 Announce Type: new Abstract: ProvenanceWidgets is an existing JavaScript library that tracks the recency and frequency of user interactions with individual UI controls (e.g., range sliders and dropdowns) and dynamically overlays this provenance onto them. In this work, we introduce SuperProvenanceWidgets, an extension to ProvenanceWidgets featuring a new SuperWidget that similarly tracks and visualizes provenance but across multiple UI controls, enabling users to understand how, when, and whether different UI controls were used. Through three example usage […]

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People think that becoming a writer is easy. In some ways, it is. All you need is a pen and paper or a computer, an idea, and the determination to write. Voila, you’re a writer now. Writing is easy; becoming serious about your writing is a whole lot harder and more complex. However, why should it be? Writers should be helping each other navigate this crazy world whenever possible. So, if you’re reading this right now, then that […]

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arXiv:2601.16333v1 Announce Type: new Abstract: Foundation models are used for many real-world applications involving language generation from temporally-ordered multimodal events. In this work, we study the ability of models to identify the most important sub-events in a video, which is a fundamental prerequisite for narrating or summarizing multimodal events. Specifically, we focus on football games and evaluate models on their ability to distinguish between important and non-important sub-events in a game. To this end, we construct a new […]

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