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Research map / Vision-language and multimodal / Visual question answering

Community-Based Question Answering via Asymmetric Multi-Faceted Ranking Network Learning

AAAI 2017 · Vision-language and multimodal › Visual question answering · approach: Universal VQA models · 57 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use AMRNL (asymmetric multi-faceted ranking with authority and following relations) instead of HSNLHSNL · Quora, 60% trainingnDCG: 0.8704 -> 0.8884Helped
use AMRNL instead of HSNLHSNL · Quora, 60% trainingPrecision@1: 0.4896 -> 0.5025Helped
use AMRNL instead of HSNLHSNL · Quora, 80% trainingAccuracy: 0.4720 -> 0.4951Helped
replace bag-of-words matching with deep semantic matching (CNTN)BOW · Quora, 80% trainingnDCG: 0.7325 -> 0.8967Helped
add answerer authority and asymmetric following network to semantic matching (AMRNL vs S-matrix)semantic matching model · Quora, 80% trainingnDCG: 0.8942 -> 0.9234Helped
vary network embedding size from 64 to 1024 and lambda from 1e-6 to 1e6 (ablation)AMRNL · Quora, 60% trainingnDCG/P@1/AccuracyMixed

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