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 391–400 of 483 papers

TitleStatusHype
ReGraP-LLaVA: Reasoning enabled Graph-based Personalized Large Language and Vision AssistantCode0
Anticipating Technical Expertise and Capability Evolution in Research Communities using Dynamic Graph TransformersCode0
LightPath: Lightweight and Scalable Path Representation LearningCode0
SeCG: Semantic-Enhanced 3D Visual Grounding via Cross-modal Graph AttentionCode0
GMNN: Graph Markov Neural NetworksCode0
Relational Deep Reinforcement LearningCode0
Column Networks for Collective ClassificationCode0
Learning the meanings of function words from grounded language using a visual question answering modelCode0
Logic Tensor Networks for Semantic Image InterpretationCode0
FlexMol: A Flexible Toolkit for Benchmarking Molecular Relational LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified