arXiv:2602.16722v1 Announce Type: new Abstract: This paper introduces a real-time method for reverse engineering a vehicle’s CAN bus without prior knowledge of the vehicle or its CAN system. By comparing inertial measurement and CAN data during significant vehicle events, the method accurately identified the CAN channels associated with the accelerator pedal, brake pedal, and steering wheel. Utilizing an IMU, CAN module, and event-driven software architecture, the system was validated using prerecorded serialized data from previous studies. This data, […]

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Following the successful event at Abu Dhabi, Riyadh is also going to become the “Mecca of Blockchain” as the Global Blockchain Show is making its comeback there. The global event shall take place on the 9th-10th of February 2026 at the Malfa hall and will commemorate the attendance of industry stalwarts and thought leaders across the Web3 industry. It will provide an innovative platform where cutting-edge technologies will collide with the worlds of business and finance. Organized by […]

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arXiv:2602.06218v1 Announce Type: new Abstract: Vision-language models (VLMs) align images and text with remarkable success, yet the geometry of their shared embedding space remains poorly understood. To probe this geometry, we begin from the Iso-Energy Assumption, which exploits cross-modal redundancy: a concept that is truly shared should exhibit the same average energy across modalities. We operationalize this assumption with an Aligned Sparse Autoencoder (SAE) that encourages energy consistency during training while preserving reconstruction. We find that this inductive […]

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I built WM Arena (arena.worldflux.ai), an interactive benchmark for visual world models on the Atari 100k suite. Three modes: – Visual Explorer: side-by-side real vs predicted frames across 26 games – Blind Battle: ELO-ranked voting on anonymous model outputs – Real or Predicted? Quiz: a perception test Currently evaluating DIAMOND (NeurIPS ’24 Spotlight), TWISTER (ICLR ’25), IRIS (ICLR ’23), and STORM (NeurIPS ’23). Every model runs its official code at a pinned commit. No re-implementations. Try it: arena.worldflux.ai […]

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arXiv:2603.16910v1 Announce Type: new Abstract: As autonomous agents increasingly operate in real-world digital ecosystems, understanding how they coordinate, form institutions, and accumulate shared culture becomes both a scientific and practical priority. This paper introduces TerraLingua, a persistent multi-agent ecology designed to study open-ended dynamics in such systems. Unlike prior large language model simulations with static or consequence-free environments, TerraLingua imposes resource constraints and limited lifespans for the agents. As a result, agents create artifacts that persist beyond individuals, […]

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arXiv:2603.20327v1 Announce Type: new Abstract: Video world models trained with Joint Embedding Predictive Architectures (JEPA) acquire rich spatiotemporal representations by predicting masked regions in latent space rather than reconstructing pixels. This removes the visual verification pathway of generative models, creating a structural interpretability gap: the encoder has learned physical structure inaccessible in any inspectable form. Existing probing methods either operate in continuous space without a structured intermediate layer, or attach generative components whose parameters confound attribution of behavior […]

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The life of a prescription at Amazon Pharmacy From pricing estimation and regulatory compliance to inventory management and chatbot assistants, machine learning models help Amazon Pharmacy customers stay healthy and save time and money. Conversational AI Alexandre Alves Anita Vila September 30, 01:32 PM October 02, 11:42 AM Pharmacies play a vital role in ensuring patients health, but the process of dispensing medications is far more complex than it may appear. At Amazon Pharmacy, we are using artificial […]

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arXiv:2604.13046v1 Announce Type: new Abstract: Data-driven systems depend on task-relevant data, yet data collection pipelines remain passive and indiscriminate. Continuous logging of multimodal sensor streams incurs high storage costs and captures irrelevant data. This paper proposes a declarative framework for intent-driven, on-device data collection that enables selective collection of multimodal sensor data based on high-level user requests. The framework combines natural language interaction with a formally specified domain-specific language (DSL). Large language models translate user-defined requirements into verifiable […]

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