SOURCE-LINKED INTELLIGENCE
FRAME: Factored Retrieval via Attribute Readouts for Object-Centric Scene Memory
Language-guided robots need persistent scene memories to follow instructions, revisit objects, and resolve references to objects encountered over time. While much of language-guided scene-memory retrieval has emphasized spatial or relational references, many everyday object references specify objects by multiple persistent attributes, such as category, material, size, or surface appearance. We formalize this problem as attribute-compositional retrieval, where a fixed object-centric scene memory is queried with natural language to retrieve the object satisfying the requested attributes. To inve
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-08T15:26:00.000Z
First collected: 2026-09-20T20:02:11.508Z. This is not the publication date.