Aug 2026· International Conference on Automated Software Engineering· Vol 33· 0 citations· 46 references
TL;DR
NavAI is an extensible navigation framework that leverages large language models (LLMs) to support both basic action commands and multi-step goal-oriented navigation through an application-agnostic screenshot-and-control interface and explores optimization strategies for virtual scene understanding and navigation goal decision making.
The proposed DevGRU navigation system employs an action predictor that generates collision-aware future trajectories, enabling effective avoidance of immediate obstacles and has a relatively small number of trainable parameters, resulting in the fastest inference time among the baselines.
Kyung Min Han, Eunsom Kim, Young J. Kim· IEEE Robotics and Automation...· 0 citations
ZONDA, a zero-shot object navigation with dynamic avoidance framework, integrates three core components and can maintain robust navigation on the dynamic benchmark HM3D-DYNA compared to the existing baseline.
This work proposes TAMP-Nav, a unified framework for efficient embodied navigation that dynamically triggers Chain-of-Thought and retains high-fidelity memory only at critical nodes, compressing redundant trajectories into lightweight Space-Time Indicators, thereby preserving critical historical information and enhanci...
Hongyan Feng, Sun-Lai Chen, Xuan-Yu Liu et al.· 1 citation
SoftNav is introduced, which injects entity-level 3D continuous representations -- one token per detected object or frontier -- into a VLM's hidden space as soft tokens through a lightweight projector, enabling transferable navigation with minimal training.
Yi Wu, Junjie An, Xiao Liu et al.· arXiv.org· 0 citations
FILD-Nav extracts task-relevant landmarks from instructions and incorporates landmark semantics into both waypoint prediction and topological planning, which improves waypoint relevance and enables more effective long-horizon navigation.
Chuan-Ye Hu, Lu-Lu Liu, Huai-Wei Si et al.· Proceedings of the Thirty-Fi...· 0 citations
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
