Hypothesis Graph Refinement represents frontier predictions as revisable hypothesis nodes and applies verification-driven cascade correction to prune erroneous subgraphs, achieving 72.41% success and 56.22% SPL on GOAT-Bench.
In: Proceedings of the IEEE conference on computer vision and pattern recognition
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Rule-VLN injects 177 regulatory signs into Touchdown-scale urban graphs; SNRM’s VLM perception plus mental-map detours cuts constraint violations ~19% and raises task completion ~6% zero-shot.
Phi-Nav generates path-level hindsight instructions from on-policy exploration trajectories to supply additional semantic supervision for vision-language navigation agents.
Privatar partitions VR avatar reconstruction via frequency-domain decomposition, keeping sensitive components local and offloading the rest with distribution-aware minimal perturbation noise, achieving 2.37x throughput with provable privacy.
An asynchronous fast-slow dual-system with DiT action modeling and time-weighted loss doubles unseen aerial VLN success rates and halves decision latency in simulation.
citing papers explorer
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Hypothesis Graph Refinement: Hypothesis-Driven Exploration with Cascade Error Correction for Embodied Navigation
Hypothesis Graph Refinement represents frontier predictions as revisable hypothesis nodes and applies verification-driven cascade correction to prune erroneous subgraphs, achieving 72.41% success and 56.22% SPL on GOAT-Bench.
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Rule-VLN: Bridging Perception and Compliance via Semantic Reasoning and Geometric Rectification
Rule-VLN injects 177 regulatory signs into Touchdown-scale urban graphs; SNRM’s VLM perception plus mental-map detours cuts constraint violations ~19% and raises task completion ~6% zero-shot.
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Path-level Hindsight Instructions for Semantic Exploration in Vision-Language Navigation
Phi-Nav generates path-level hindsight instructions from on-policy exploration trajectories to supply additional semantic supervision for vision-language navigation agents.
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Dual-Anchoring: Addressing State Drift in Vision-Language Navigation
Privatar partitions VR avatar reconstruction via frequency-domain decomposition, keeping sensitive components local and offloading the rest with distribution-aware minimal perturbation noise, achieving 2.37x throughput with provable privacy.
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FSD-VLN: Fast-Slow Dual-System Modeling for Aerial Long-Horizon Vision-Language Navigation
An asynchronous fast-slow dual-system with DiT action modeling and time-weighted loss doubles unseen aerial VLN success rates and halves decision latency in simulation.