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 126–150 of 483 papers

TitleStatusHype
MUREL: Multimodal Relational Reasoning for Visual Question AnsweringCode0
One-Shot Relational Learning for Knowledge GraphsCode0
Mandolin: A Knowledge Discovery Framework for the Web of DataCode0
Logic Tensor Networks for Semantic Image InterpretationCode0
Mapping Natural Language Commands to Web ElementsCode0
Differentially Private Relational Learning with Entity-level Privacy GuaranteesCode0
LightPath: Lightweight and Scalable Path Representation LearningCode0
Leveraging Relational Information for Learning Weakly Disentangled RepresentationsCode0
Associative TransformerCode0
Lifted Inference beyond First-Order LogicCode0
MDE: Multiple Distance Embeddings for Link Prediction in Knowledge GraphsCode0
On Inductive Abilities of Latent Factor Models for Relational LearningCode0
A simple neural network module for relational reasoningCode0
Compositional Language Understanding with Text-based Relational ReasoningCode0
Language-Conditioned Graph Networks for Relational ReasoningCode0
Knowledge Graph Completion via Complex Tensor FactorizationCode0
Large Class Separation is not what you need for Relational Reasoning-based OOD DetectionCode0
Adversarial Sets for Regularising Neural Link PredictorsCode0
Few-shot Knowledge Graph Relational Reasoning via Subgraph AdaptationCode0
CommonGen: A Constrained Text Generation Challenge for Generative Commonsense ReasoningCode0
Interpretable preference learning: a game theoretic framework for large margin on-line feature and rule learningCode0
Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge GraphsCode0
AS3D: 2D-Assisted Cross-Modal Understanding with Semantic-Spatial Scene Graphs for 3D Visual GroundingCode0
Complementary Structure-Learning Neural Networks for Relational ReasoningCode0
Learning the meanings of function words from grounded language using a visual question answering modelCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified