SOTAVerified

Relational Reasoning

The goal of Relational Reasoning is to figure out the relationships among different entities, such as image pixels, words or sentences, human skeletons or interactive moving agents.

Source: Social-WaGDAT: Interaction-aware Trajectory Prediction via Wasserstein Graph Double-Attention Network

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 261–270 of 483 papers

TitleStatusHype
Relational Learning for Skill Preconditions—0
Multi-choice Relational Reasoning for Machine Reading Comprehension—0
Open-Ended Multi-Modal Relational Reasoning for Video Question AnsweringCode0
Graph-Based Knowledge Integration for Question Answering over Dialogue—0
Modelling Compositionality and Structure Dependence in Natural Language—0
Modular Graph Attention Network for Complex Visual Relational Reasoning—0
Towards Abstract Relational Learning in Human Robot Interaction—0
Classification by Attention: Scene Graph Classification with Prior Knowledge—0
Skeleton-based Relational Reasoning for Group Activity Analysis—0
Distilling Structured Knowledge for Text-Based Relational Reasoning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified