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 61–70 of 483 papers

TitleStatusHype
Graph-Based Social Relation ReasoningCode1
Beyond Graph Neural Networks with Lifted Relational Neural NetworksCode1
Learning Reasoning Strategies in End-to-End Differentiable ProvingCode1
Generative 3D Part Assembly via Dynamic Graph LearningCode1
Self-Supervised Relational Reasoning for Representation LearningCode1
Reasoning with Latent Structure Refinement for Document-Level Relation ExtractionCode1
Scalable Multi-Hop Relational Reasoning for Knowledge-Aware Question AnsweringCode1
Machine Number Sense: A Dataset of Visual Arithmetic Problems for Abstract and Relational ReasoningCode1
Deep Relational Reasoning Graph Network for Arbitrary Shape Text DetectionCode1
Evaluating Logical Generalization in Graph Neural NetworksCode1
Show:102550
← PrevPage 7 of 49Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified