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 121–130 of 483 papers

TitleStatusHype
Automatic Generation of Contrast Sets from Scene Graphs: Probing the Compositional Consistency of GQACode0
Learning the meanings of function words from grounded language using a visual question answering modelCode0
Large Class Separation is not what you need for Relational Reasoning-based OOD DetectionCode0
Language-Conditioned Graph Networks for Relational ReasoningCode0
Recurrent Relational Networks for complex relational reasoningCode0
Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge GraphsCode0
Knowledge Graph Completion via Complex Tensor FactorizationCode0
Leveraging Relational Information for Learning Weakly Disentangled RepresentationsCode0
Inferring Scientific Cross-Document Coreference and Hierarchy with Definition-Augmented Relational ReasoningCode0
Interaction Relational Network for Mutual Action RecognitionCode0
Show:102550
← PrevPage 13 of 49Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified