GeoCloak: An Agentic Framework for Semantics-Preserving Geolocation Privacy via Peripheral Clue Manipulation
GeoCloak cuts LVLM city-level geolocation accuracy from 41.2% to 9.9% while preserving image meaning.
Stories per day · 30 days
2 RSS
9 stories, newest first · one card per story
Stories tagged #lvlm
SpatialASM: Internalizing Active Mentalization for Spatial Reasoning
SpatialASM trains vision-language models to plan viewpoints and imagine scenes, improving accuracy on seven spatial benchmarks.
SpatialASM: Internalizing Active Mentalization for Spatial Reasoning
SpatialASM trains vision-language models to plan viewpoints and simulate scenes for spatial reasoning.
SpatialCORE: Confidence-Aware Grounded Spatial Reasoning in Large Vision--Language Models
SpatialCORE uses grounding confidence as a reward so vision-language models reason from accurately localized objects.
Soft Spatial Reasoning
Soft Spatial Reasoning lets vision-language models mix token embeddings instead of committing to one spatial token.
VideoLoop: Looped Working Memory Against Semantic Thrashing in Long-Form Video Agents
VideoLoop rewrites bounded memory so long-video agents avoid semantic thrashing, gaining 4.2 points.
Still There, No Longer Seen: Exposing Compression-Induced Risk in Large Vision-Language Models
CIRA induces LVLM failures only after visual-token compression, with a 20.35% mean failure rate.
Mind the Spike: Mechanisms and Brittleness of Visual Massive Activations in Large Vision-Language Models
Visual activation spikes in vision-language models are brittle and can be created or removed with tiny image perturbations.
SpatialBlock: Enhancing Spatial Intelligence in LVLMs via Synthetic Block-Stacking Problem
Researchers release SpatialBlock-15k, a synthetic block-stacking dataset that improves 3D spatial reasoning in large vision-language models without dense geometric annotations.