CoFL-S: Spatially Queryable Sector Flow Fields for Local Language-Conditioned Navigation

arXiv:2607.02222 · cs.RO, cs.AI · Submitted 2026-07-02 · Read on arXiv

cs.RO, cs.AI

Submitted: 2026-07-02

Updated: 2026-09-25

Terminology

• Benchmark — 18× in this paper · explained in 2 episodes
• Grounding — 11× in this paper · explained in 3 episodes
• Transformer — 9× in this paper · explained in 2 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Alignment — 5× in this paper · explained in 1 episode
• Vision-Language Navigation — 5× in this paper
• Ablation Studies — 3× in this paper · explained in 1 episode
• CVF International Conference on Computer Vision — 3× in this paper
• Success Rate — 3× in this paper
• Blocked-Step Rate — 2× in this paper
• Embodied AI — 2× in this paper · explained in 2 episodes
• Heading Smoothness — 2× in this paper
• Oracle Success — 2× in this paper
• Steering — 2× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Closed-Loop Control — 1× in this paper · explained in 3 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Empirical Methods in Natural Language Processing — 1× in this paper
• Failure Modes — 1× in this paper · explained in 3 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• World Model — 1× in this paper · explained in 7 episodes
• Zero-Shot Transfer — 1× in this paper · explained in 4 episodes

Sources

• CoFL: Continuous Flow Fields for Language-Conditioned Navigation
• SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features

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