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 226–250 of 483 papers

TitleStatusHype
T-GAP: Learning to Walk across Time for Temporal Knowledge Graph Completion—0
Factor Graph Molecule Network for Structure Elucidation—0
Fusing Context Into Knowledge Graph for Commonsense Question AnsweringCode1
Relational Learning for Skill Preconditions—0
Multi-choice Relational Reasoning for Machine Reading Comprehension—0
Graph-Based Knowledge Integration for Question Answering over Dialogue—0
Open-Ended Multi-Modal Relational Reasoning for Video Question AnsweringCode0
Self-Supervised Time Series Representation Learning by Inter-Intra Relational ReasoningCode1
Play Fair: Frame Attributions in Video ModelsCode1
Modular Graph Attention Network for Complex Visual Relational Reasoning—0
Modelling Compositionality and Structure Dependence in Natural Language—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
Learning Explainable Linguistic Expressions with Neural Inductive Logic Programming for Sentence Classification—0
Distilling Structured Knowledge for Text-Based Relational Reasoning—0
Modeling Content and Context with Deep Relational LearningCode0
The Curious Case of Stacking Boosted Relational Dependency Networks—0
Analogical and Relational Reasoning with Spiking Neural Networks—0
BayReL: Bayesian Relational Learning for Multi-omics Data IntegrationCode1
Scale-Localized Abstract ReasoningCode1
Conditional Hybrid GAN for Sequence Generation—0
Visual Relationship Detection with Visual-Linguistic Knowledge from Multimodal RepresentationsCode1
Learning from Protein Structure with Geometric Vector PerceptronsCode1
LowFER: Low-rank Bilinear Pooling for Link PredictionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified