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ENCP: Episode-Normalized Conformal Prediction for Vision-and-Language Navigation

Paper recorded by Signals 4 on 2026-09-15 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-15 on arXiv · recorded by Signals 4 on 2026-09-16

Category: cs.AI · 人工智能 · first seen 2026-09-16

Abstract

Uncertainty estimation for Vision-Language-Navigation (VLN) models is a critical task since it can help identify ambiguous and unreliable predictions, enabling agents to make safer navigation decisions. As one of the most advanced uncertainty estimation frameworks, conformal prediction (CP) offers a promising approach for uncertainty estimation in VLN. However, given that VLN agent requires a sequ

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#46 most recent of 300 cs.AI papers we have recorded · ↑ newer: LACE: Layer-Wise Compression for Dynamic Frame Rate Codecs · ↓ older: Verifiable Social Reasoning for LLM Assistants
Cite this page: ENCP: Episode-Normalized Conformal Prediction for Vision-and-Language Navigation: the #46 most recent of 300 cs.AI papers we have recorded (as of 2026-09-15). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/encp-episode-normalized-conformal-prediction-for-vision-and-language-navigation.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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