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 401–410 of 483 papers

TitleStatusHype
Visual Reasoning in Object-Centric Deep Neural Networks: A Comparative Cognition ApproachCode0
Large Class Separation is not what you need for Relational Reasoning-based OOD DetectionCode0
Language-Conditioned Graph Networks for Relational ReasoningCode0
Mandolin: A Knowledge Discovery Framework for the Web of DataCode0
Mapping Natural Language Commands to Web ElementsCode0
Cognitive Knowledge Graph Reasoning for One-shot Relational LearningCode0
MDE: Multiple Distance Embeddings for Link Prediction in Knowledge GraphsCode0
Bridging Generative and Discriminative Learning: Few-Shot Relation Extraction via Two-Stage Knowledge-Guided Pre-trainingCode0
Meta Relational Learning for Few-Shot Link Prediction in Knowledge GraphsCode0
Relational Learning for Joint Head and Human DetectionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified