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 421–430 of 483 papers

TitleStatusHype
Relational reasoning and generalization using non-symbolic neural networksCode0
Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge GraphsCode0
Automatic Generation of Contrast Sets from Scene Graphs: Probing the Compositional Consistency of GQACode0
The relational processing limits of classic and contemporary neural network models of language processingCode0
Skews in the Phenomenon Space Hinder Generalization in Text-to-Image GenerationCode0
VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural LanguageCode0
Differentially Private Relational Learning with Entity-level Privacy GuaranteesCode0
Relational recurrent neural networksCode0
AS3D: 2D-Assisted Cross-Modal Understanding with Semantic-Spatial Scene Graphs for 3D Visual GroundingCode0
Double Equivariance for Inductive Link Prediction for Both New Nodes and New Relation TypesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified