arXiv (All)
open access
Belief-Aware VLM Model for Human-like Reasoning
Traditional neural network models for intent inference rely heavily on observable states and struggle to generalize across diverse tasks and dynamic environments. Recent advances in Vision Language Models (VLMs) and Vision Language Action (VLA) models introduce common-sense reasoning through large-s
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
- Soft Spatial Reasoning#1143318
- Recompose and Refine Latent Reasoning Flows for Vision-Language-Action Models#1249514
- Logic-VLA: A Temporal Logic Conditioned Vision-Language-Action Model#659120
- Logic-VLA: A Temporal Logic Conditioned Vision-Language-Action Model#656984
- SPLIT-RL: Staged Perception-Language Reasoning Training with Claim-Level Advantages#1247816
Record · ID 1387951
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