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 111–120 of 483 papers

TitleStatusHype
Leveraging Relational Information for Learning Weakly Disentangled RepresentationsCode0
Object-Oriented Dynamics Learning through Multi-Level AbstractionCode0
Disentangling and Integrating Relational and Sensory Information in Transformer ArchitecturesCode0
Breakpoint Transformers for Modeling and Tracking Intermediate BeliefsCode0
Bridging Generative and Discriminative Learning: Few-Shot Relation Extraction via Two-Stage Knowledge-Guided Pre-trainingCode0
Distributed Associative Memory Network with Memory Refreshing LossCode0
R5: Rule Discovery with Reinforced and Recurrent Relational ReasoningCode0
ORCHARD: A Benchmark For Measuring Systematic Generalization of Multi-Hierarchical ReasoningCode0
Coresets for Relational Data and The ApplicationsCode0
Automatic Generation of Contrast Sets from Scene Graphs: Probing the Compositional Consistency of GQACode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified