arXiv (All)
open access
Long Time No See: Benchmarking VLMs for Out-of-Sight Spatiotemporal Reasoning in Egocentric Videos
Real-world AI systems must reason about objects that are no longer visible: an AR assistant guiding a user back to an object used earlier, a household robot retrieving an item someone put away. This requires not just recalling where an object was last seen, but updating its state when it is moved an
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- FiberTune: Preserving Action-Fiber Visual Residuals in Vision-Language-Action Fine-Tuning#1084240
- Residual Optimal Transport-Based Experts Collaboration Towards Modality-Aware Infrared-Visible Object Detection#926430
- Seeing Things as They Are#700173
- Learning from Private and Public Observation of Other's Actions#499536
- QSV: Quat-Sphere-Vision for Coupled Quaternion Attention on Spherical Lattices#1104791
Record · ID 1128892
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive