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KERM: Knowledge Enhanced Reasoning for Vision-and-Language Navigation

CVPR 2023 · Vision-language and multimodal › Robot action and navigation · approach: Reasoning-enhanced vision-language navigation · 53 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add retrieved knowledge facts and KERM reasoning to DUETDUET · REVERIE Val UnseenSR: 46.98 -> 50.44Helped
Add retrieved knowledge facts and KERM reasoning to DUETDUET · R2R Val UnseenSR: 71.52 -> 71.95Helped
Add retrieved knowledge facts and KERM reasoning to DUETDUET · SOON Val UnseenSR: 36.28 -> 38.05Helped
Add purification (ablation)KERM with both interaction modules · REVERIE Val UnseenSR: 49.43 -> 50.44Helped
Add vision-fact interaction (ablation)KERM with purification and history-fact interaction · REVERIE Val UnseenSR: 49.33 -> 50.44Helped
Add history-fact interaction (ablation)KERM with purification and vision-fact interaction · REVERIE Val UnseenSR: 48.96 -> 50.44Helped
Replace object-centric features with retrieved facts (ablation)Baseline on REVERIE · REVERIE Val UnseenSR: 49.73 -> 50.44Helped
Add object-centric features (ablation)Baseline on REVERIE · REVERIE Val UnseenSR: 46.98 -> 49.73Helped
Use 5 cropped sub-regions instead of 1 (ablation)KERM · REVERIE Val UnseenSR: 49.67 -> 50.44Helped
Use 9 cropped sub-regions instead of 5 (ablation)KERM · REVERIE Val UnseenSR: 50.44 -> 48.99Hurt
Use KERM pretraining with augmented data before fine-tuning (ablation)KERM · REVERIE Val UnseenSR: 49.02 -> 50.44Helped
Use knowledge-enhanced features in the fine-scale encoder (ablation)DUET-fine · REVERIE Val UnseenSR: 28.86 -> 30.80Helped

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