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 321–330 of 483 papers

TitleStatusHype
Compensating Supervision Incompleteness with Prior Knowledge in Semantic Image InterpretationCode1
Relational Learning for Joint Head and Human DetectionCode0
Deep Message Passing on Sets—0
RuDaS: Synthetic Datasets for Rule Learning and Evaluation ToolsCode0
PARN: Position-Aware Relation Networks for Few-Shot LearningCode0
Relationships from Entity StreamCode0
Meta Relational Learning for Few-Shot Link Prediction in Knowledge GraphsCode0
The Impact of Semantic Linguistic Features in Relation Extraction: A Logical Relational Learning Approach—0
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from TextCode1
Hyperlink Regression via Bregman Divergence—0
Show:102550
← PrevPage 33 of 49Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified