Instruction understanding is reframed as an evolving Instruction-as-State variable conditioned on perceptual state and realized via the S-EGIU coarse-to-fine framework, reporting a +2.68% SPL gain on REVERIE Test Unseen.
Camera-aware la- bel refinement for unsupervised person re-identification
4 Pith papers cite this work. Polarity classification is still indexing.
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2026 4representative citing papers
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.
SDB balances behavioral diversity and learning stability in VLN self-improvement by expanding decisions into latent hypotheses, performing reliability-aware aggregation, and applying a regularizer, yielding gains such as SPL 33.73 to 35.93 on REVERIE val-unseen.
HRNav decomposes image-goal navigation into VLM-based short-horizon planning and RL-based execution with a wandering suppression penalty to improve performance in complex unseen settings.
citing papers explorer
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Instruction-as-State: Environment-Guided and State-Conditioned Semantic Understanding for Embodied Navigation
Instruction understanding is reframed as an evolving Instruction-as-State variable conditioned on perceptual state and realized via the S-EGIU coarse-to-fine framework, reporting a +2.68% SPL gain on REVERIE Test Unseen.
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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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The Essence of Balance for Self-Improving Agents in Vision-and-Language Navigation
SDB balances behavioral diversity and learning stability in VLN self-improvement by expanding decisions into latent hypotheses, performing reliability-aware aggregation, and applying a regularizer, yielding gains such as SPL 33.73 to 35.93 on REVERIE val-unseen.
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Think before Go: Hierarchical Reasoning for Image-goal Navigation
HRNav decomposes image-goal navigation into VLM-based short-horizon planning and RL-based execution with a wandering suppression penalty to improve performance in complex unseen settings.