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Fewer, Better Frames: A Compute-Normalized Proof of Concept for Coherence-First World-Model Rendering with Model-Guided FSR4 Frame Generation
arXiv:2606.02586v1 Announce Type: new Abstract: World models are often evaluated by native frame cadence, but higher nominal frame rate can trade away long-horizon scene stability. This article reports an independent proof of concept implemented using Overworld's Waypoint-1.5 family and WorldEngine runtime on a Windows fallback stack with ONNX Runtime + DirectML and an FSR4 DX12 bridge. The tested coherence-first branch generates higher-context anchor frames at a 15 FPS presentation-timeline...
TROPHIES: Temporal Reconstruction of Places, Humans, and Cameras from Multi-view Videos
arXiv:2606.02350v1 Announce Type: new Abstract: Reconstructing humans and their surrounding environments in a globally consistent 4D space is essential for comprehensive perception. However, prior works typically assume single-view inputs or decouple humans, scenes, and cameras, making them unable to recover coherent geometry, stable motion, and physically aligned trajectories. These limitations motivate us to introduce a new task: unified human-scene-camera reconstruction from multi-view...
Unveiling the Unknown: Open Vocabulary Object Detection with Scene Graphs
arXiv:2606.05916v1 Announce Type: new Abstract: Open-vocabulary object detection seeks to identify novel object categories that were not part of the training data. Many knowledge distillation-based approaches have shown promising performance by transferring knowledge from pre-trained vision-language models to object detection. However, these methods often overlook structured, image-specific relationships between objects, such as interactions and spatial arrangements.
GeoSem-WAM: Geometry- and Semantic-Aware World Action Models
arXiv:2606.03188v1 Announce Type: new Abstract: Recent World Action Models (WAMs) have demonstrated impressive capabilities in embodied decision-making. However, whether their effectiveness stems from explicit future imagination during inference or representation learning induced by predictive training remains an open question. Emerging evidence suggests the primary advantage lies in learning robust latent representations rather than generating future observations at test time.
Pitsford plane crash horror as aircraft plunges into field with huge emergency response
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2 wives, domestic abuse, deadly plot: Chilling details in ex-Congress sarpanch's family murder
Police said Friday the deaths of a 52-year-old former sarpanch and three members of his family, whose charred bodies were found inside a burnt SUV near Shri Rampura village in Arai area of Ajmer district Thursday morning, were not accidental but a planned quadruple murder. Investigators said the killings were allegedly carried out by the man’s first wife and their two children, including a minor son. Bodies of Ram Singh Choudhary, former sarpanch of Borada Gram Panchayat and a Congress...
Global-Local Monte Carlo Tree Search in Vision-Language Models for Text-to-3D Indoor Scene Generation
arXiv:2606.06002v1 Announce Type: new Abstract: Large Vision-Language Models have achieved significant reasoning performance in various tasks. However, there are few studies on text-to-3D indoor scene generation with LVLMs. The main challenge is that prevailing LVLM-based methods employ chain-of-thought sequential decision mechanisms that cannot revise earlier decisions, causing error propagation.
Global-Local Monte Carlo Tree Search in Vision-Language Models for Text-to-3D Indoor Scene Generation
arXiv:2606.06002v2 Announce Type: replace Abstract: Large Vision-Language Models have achieved significant reasoning performance in various tasks. However, there are few studies on text-to-3D indoor scene generation with LVLMs. The main challenge is that prevailing LVLM-based methods employ chain-of-thought sequential decision mechanisms that cannot revise earlier decisions, causing error propagation.
AHA-WAM:Asynchronous Horizon-Adaptive World-Action Modeling with Observation-Guided Context Routing
arXiv:2606.09811v1 Announce Type: new Abstract: World-action models have emerged as a promising paradigm for robot manipulation, jointly modeling visual scene dynamics and actions to inject physical priors into policy learning. However, existing world-action models couple world prediction and action execution at the same temporal resolution, forcing the world branch to model near-term frame variations that are redundant and weakly informative. We posit that strictly binding world prediction...
Coarse-to-fine Hierarchical Architecture with Sequential Mamba for Brain Reconstruction
Announce Type: new Abstract: Understanding the relationship between deep visual representations and the human visual system is a fundamental challenge in computational neuroscience. While modern vision models achieve strong performance in image recognition, their correspondence with the hierarchical organization of the human visual cortex remains an open question. In this study, we propose CHASMBrain, a novel hierarchical two-stage framework for image-to-fMRI encoding.