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Vision-Language Navigation With Self-Supervised Auxiliary Reasoning Tasks

CVPR 2020 · Vision-language and multimodal › Robot action and navigation · approach: Reasoning-enhanced vision-language navigation · 215 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add all four auxiliary reasoning tasks (ablation)VLN baseline · R2R val seenSPL (%): 55.87 -> 58.89Helped
Add all four auxiliary reasoning tasks (ablation)VLN baseline · R2R val unseenSPL (%): 42.89 -> 45.67Helped
Add cross-modal matching alone (ablation)VLN baseline · R2R val seenSPL (%): 55.87 -> 53.55Hurt
Add trajectory retelling (ablation)VLN baseline · R2R val unseenSPL (%): 42.89 -> 45.24Helped
Add progress estimation (ablation)VLN baseline · R2R val unseenSPL (%): 42.89 -> 44.74Helped
Add angle prediction (ablation)VLN baseline · R2R val unseenSPL (%): 42.89 -> 43.77No clear effect
Add all four auxiliary tasks alongside back-translation (ablation)VLN baseline + back-translation · R2R val seenSPL (%): 61.37 -> 67.17Helped
Use teacher forcing instead of Matching Critic for trajectory retelling (ablation)VLN baseline · R2R val unseenSPL (%): 43.44 -> 45.24Helped
Use teacher forcing instead of student forcing for trajectory retelling (ablation)VLN baseline · R2R val unseenSPL (%): 43.78 -> 45.24Helped
Share context in teacher-forced trajectory retelling (ablation)VLN baseline · R2R val unseenSPL (%): 45.24 -> 44.47Hurt
Use step-percentage progress labels with BCE rather than MSE loss (ablation)VLN progress estimator · R2R val seenSPL (%): 50.81 -> 57.15Helped
Use step-percentage progress labels with BCE rather than MSE loss (ablation)VLN progress estimator · R2R val unseenSPL (%): 43.16 -> 44.74Helped

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