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Pulse · dig.watch

dig.watch · Nov 5

Apple includes AI Agent risk factors to SEC Form 10‑K filing

Apple Inc. added new risk factors concerning autonomous AI agents to its SEC filing, warning that such agents could act unpredictably.

Pulse · venturebeat.com

venturebeat.com · Nov 4

Ex-Googlers' new Apache 2.0 model Ripple-65B Preview claims the U.S. open coding lead on two major benchmarks

The appeal of Ricursive Intelligence's Ripple-65B Preview is the combination of downloadable weights, a permissive license, competitive company-reported coding results and a low-priced hosted entry point.

Pulse · hoodline.com

hoodline.com · Nov 4

NYC-Tel Aviv Startup Sentra Lands $150M as Rogue AI Agents Spook Corporations

Sentra says the past year brought more than 300% year-over-year growth, a surge it attributes to enterprises racing to deploy AI agents without fully understanding what those agents can access. The company's pitch centers on a platform that finds and classifies data across cloud,

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Top picks this weekarXiv

arXiv

Nov 3

DreamX: Video Diffusion Model is a Universal Latent Action Learner

Learning a universal action representation from video requires modeling dynamics that are consistent across different executions of the same action yet invariant to changes in embodiment and appearance. Existing latent action models infer actions from visual transitions, but their representations often entangle the underlying action with irrelevant visual variations, limiting transfer across embodiments. We introduce DreamX, which repurposes a pretrained video diffusion model as a universal latent action learner. Our approach extracts compact latent actions from the video model's rich spatiotemporal features, compressing each latent video frame by $\boldsymbol{300\times}$ ($\boldsymbol{1{,}200 \rightarrow 4}$ tokens). In addition, by leveraging the video model's generative prior, these latent actions capture action-relevant dynamics disentangled from visual appearance. The resulting latent space serves as a shared action interface across embodiments (human and robot), environments, and action parameterizations. On LARY-Bench, DreamX achieves state-of-the-art performance among latent action models. Moreover, actions encoded in one setting remain effective in another: the latent…

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arXiv

Sep 21

U-PEN Mamba: Progressive Expansion with Selective State-Space Modeling for Efficient Retinal Vessel Segmentation

Accurate retinal vessel segmentation is important for computer-aided ophthalmic analysis, yet thin vessels, low contrast, and severe foreground-background imbalance remain challenging for encoder-decoder networks. This paper presents U-PEN Mamba, a U-shaped retinal vessel…

arXiv

Sep 21

Q-DEQ: Discrete Solving and Quantization for Deep Equilibrium Models in Time Series Forecasting under Edge Deployment Coding Constraints

Edge deployment motivates forecasting models with compact parameter storage and low-bit representations. Deep equilibrium models (DEQs) obtain implicit depth by repeatedly applying a shared layer, reducing the parameter cost of explicit layer stacking. Their usual Anderson…

arXiv

Sep 21

Graph-to-Grid (G2G): Continuous-Coordinate Feature Painting for Soccer Pass Surfaces

Dense pass surfaces give, for every pitch cell, whether a pass played there would arrive, whether the carrier would choose it, and what the possession would then be worth. The networks that draw them read the state as a raster of per-cell counts, losing where inside a cell each…

arXiv

Sep 21

Structured Decomposition for Reliable LLM-Generated Access Control Policies

This paper presents an LLM-based system that translates natural-language access control policies (NLACPs) into executable Rego code for Open Policy Agent (OPA). It provides a modular, end-to-end pipeline for policy detection, component extraction, schema validation, linting,…

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