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

Showing 426450 of 483 papers

TitleStatusHype
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
Zero-Shot Relational Learning for Multimodal Knowledge GraphsCode0
Relation Network for Multi-label Aerial Image ClassificationCode0
Distributed Associative Memory Network with Memory Refreshing LossCode0
MUREL: Multimodal Relational Reasoning for Visual Question AnsweringCode0
Interpretable preference learning: a game theoretic framework for large margin on-line feature and rule learningCode0
Relationships from Entity StreamCode0
When can transformers reason with abstract symbols?Code0
VGStore: A Multimodal Extension to SPARQL for Querying RDF Scene GraphCode0
RelNN: A Deep Neural Model for Relational LearningCode0
A simple neural network module for relational reasoningCode0
Object-Oriented Dynamics Learning through Multi-Level AbstractionCode0
Temporal Relational Reasoning in VideosCode0
OCRT: Boosting Foundation Models in the Open World with Object-Concept-Relation TriadCode0
A Comparative Study of Distributional and Symbolic Paradigms for Relational LearningCode0
One-Shot Relational Learning for Knowledge GraphsCode0
On Inductive Abilities of Latent Factor Models for Relational LearningCode0
Representing Prior Knowledge Using Randomly, Weighted Feature Networks for Visual Relationship DetectionCode0
RESOLVE: Relational Reasoning with Symbolic and Object-Level Features Using Vector Symbolic ProcessingCode0
Spatiotemporal Covariance Neural NetworksCode0
Open-Ended Multi-Modal Relational Reasoning for Video Question AnsweringCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99Unverified