Perceptron offers an AI model that it says can help machines navigate the world while also providing in-depth visual intelligence.
Category: AI
A Human-Factors Guided Cognitive Model of Visuospatial Complexity in Embodied Active Vision
arXiv:2608.23572v1 Announce Type: cross Abstract: We propose a novel framework for the analysis of multimodal data — encompassing visual, auditory, and…
Strictly Causal Streaming Video Anomaly Detection with a Theoretically-Grounded State-Space Core
arXiv:2608.24810v1 Announce Type: new Abstract: Recent work has applied Mamba style state space models (SSMs) to video anomaly detection, yet existing…
StarHarness: Evolving Harnesses with Stratified Search for Enterprise Environments
arXiv:2608.24804v1 Announce Type: new Abstract: We present StarHarness, a framework for evolving environment-specific agent harnesses while keeping model…
A Dual-Dimensional LLM Framework for Automated Item Incidental Content Similarity Analysis in Large-Scale Assessments
arXiv:2608.24825v1 Announce Type: new Abstract: The rapid expansion of large-scale assessments and the growing adoption of automatic item generation have…
Bill Gates wants to see a robot tax and ‘Human Reserved’ jobs to mitigate harms from AI
Gates is mostly in the Responsible AI camp, but there are a few ideas in here we hadn’t heard before.
FedV-KGQA: Multi-Hop Question Answering over Vertically Partitioned Knowledge Graphs
arXiv:2608.24846v1 Announce Type: new Abstract: Real-world data for knowledge graph question answering is often distributed across different organizations…
Alibaba releases Qwen3.8-Flash-Next, targeting “ultimate cost efficiency”
Alibaba’s Qwen team is previewing the Qwen4 architecture with Qwen3.8-Flash-Next, a mixture-of-experts model that activates just 6 out of 125 billion…
Constrained Entity Selection under Partial Knowledge for LLM-Based Knowledge Graph QA
arXiv:2608.24824v1 Announce Type: new Abstract: Large language models are increasingly used for knowledge graph question answering (KGQA), but can fail to…
CAFE: Self-Improving Search Agents Need Co-Evolving Feedback
arXiv:2608.24794v1 Announce Type: new Abstract: Outcome-supervised search agents learn when and how to retrieve evidence, but terminal rewards neither…