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

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Showing 131–140 of 483 papers

TitleStatusHype
Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion—0
Graph Convolutional Networks from the Perspective of Sheaves and the Neural Tangent Kernel—0
EvolveHypergraph: Group-Aware Dynamic Relational Reasoning for Trajectory Prediction—0
Cross-Modal Causal Relational Reasoning for Event-Level Visual Question AnsweringCode1
Semantic Novelty Detection via Relational ReasoningCode1
Sparse Relational Reasoning with Object-Centric Representations—0
Video Dialog as Conversation about Objects Living in Space-TimeCode1
3D Part Assembly Generation with Instance Encoded Transformer—0
Specializing Pre-trained Language Models for Better Relational Reasoning via Network PruningCode1
Computer-aided Tuberculosis Diagnosis with Attribute Reasoning AssistanceCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified