Open and Emergent Problems in Agentic Privacy and Security: A Contextual Angle
Generative AI
Topic - Edition
Generative AI
Elegant object matching from several viewpoints The post Computer Vision: SIFT algorithm (Scale Invariant Feature Transform) appeared first on Towards Data Science.
Seventeen countries have endorsed the Kyoto Vision for AI-powered science. Its push toward autonomous discovery raises questions about computing access and how governments will turn policy ambitions into research…
Philosopher Benjamin Bratton has a much bigger way of thinking about AI: as the newest step in a billions-of-years process where matter produced life, life produced intelligence, and intelligence learned to build…
Model routing can finally be a design choice rather than a system enhancement The post How to Build a Cheap, Yet Reliable Model Router With Jev appeared first on Towards Data Science.
Nvidia’s planned Hugging Face acquisition and AMD’s World Labs deal bring both chipmakers closer to the developers and researchers shaping future AI workloads, giving them an earlier view of how compute requirements may…
arXiv:2605.17873v3 Announce Type: replace Abstract: Training long-horizon LLM agents with reinforcement learning is challenging because sparse outcome rewards reveal whether a task succeeds, but not which intermediate…
arXiv:2610.03452v1 Announce Type: new Abstract: Causal representation learning for time-series data aims to identify latent states and their causal relations from observations. In this setting, an important challenge is…
arXiv:2610.03524v1 Announce Type: cross Abstract: General-purpose Text-to-SQL systems achieve strong performance on academic benchmarks like Spider and BIRD, where schemas are relatively shallow and column values are…
arXiv:2605.06639v2 Announce Type: replace Abstract: We introduce Recursive Agent Optimization (RAO), a reinforcement learning approach for training recursive agents: agents that can spawn and delegate sub-tasks to new…
arXiv:2610.03001v1 Announce Type: new Abstract: Extracellular electrophysiology records a different set of neurons in every session. Neural foundation models embed each neuron and each session into their tokens, so…
arXiv:2610.02431v1 Announce Type: new Abstract: Deep neural networks achieve high accuracy through layered numerical transformations, yet their decisions remain difficult to audit because decision evidence is encoded in…
arXiv:2610.03529v1 Announce Type: new Abstract: Distillation has become a core primitive of large language model training, but its properties are not yet well understood. We take an entropic perspective, studying how…
arXiv:2610.02524v1 Announce Type: new Abstract: Unstructured pruning at extreme sparsity often suffers from representational collapse, causing sharp drops in accuracy. To address this, we study Backbone Contrastive…
arXiv:2505.13439v2 Announce Type: replace-cross Abstract: Autoregressive (AR) models have recently shown strong performance in image generation, where a critical component is the visual tokenizer (VT) that maps…
arXiv:2610.02808v1 Announce Type: cross Abstract: Adaptive multi-verifier systems are commonly compared through endpoint quality-cost gaps, even when the verifier catalog, availability, accounting, information…
arXiv:2610.03537v1 Announce Type: cross Abstract: Endovascular brain-computer interfaces (BCIs) avoid craniotomy but require precise device delivery through anatomically variable cerebral veins. This work presents the…
arXiv:2609.35763v4 Announce Type: replace Abstract: Distributional training provides collective supervision for one-step visual generation by matching real and generated features in frozen representation spaces. We…
arXiv:2610.00610v2 Announce Type: replace-cross Abstract: Explainable suicide-risk assessment requires models not only to estimate risk severity, but also to identify supporting language and the risk and protective…
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