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 101–150 of 483 papers

TitleStatusHype
Principled and Efficient Motif Finding for Structure Learning of Lifted Graphical ModelsCode0
Benchmarking and Understanding Compositional Relational Reasoning of LLMsCode0
An Explicitly Relational Neural Network ArchitectureCode0
Privately Learning from Graphs with Applications in Fine-tuning Large Language ModelsCode0
Probing Cross-Modal Representations in Multi-Step Relational ReasoningCode0
Optimal quadratic binding for relational reasoning in vector symbolic neural architecturesCode0
Open-Ended Multi-Modal Relational Reasoning for Video Question AnsweringCode0
ORCHARD: A Benchmark For Measuring Systematic Generalization of Multi-Hierarchical ReasoningCode0
An Insect-Inspired Randomly, Weighted Neural Network with Random Fourier Features For Neuro-Symbolic Relational LearningCode0
Recurrent Relational NetworksCode0
PARN: Position-Aware Relation Networks for Few-Shot LearningCode0
Propagation on Multi-relational Graphs for Node RegressionCode0
Coresets for Relational Data and The ApplicationsCode0
Automatic Generation of Contrast Sets from Scene Graphs: Probing the Compositional Consistency of GQACode0
MUREL: Multimodal Relational Reasoning for Visual Question AnsweringCode0
Distributed Associative Memory Network with Memory Refreshing LossCode0
Object-Oriented Dynamics Learning through Multi-Level AbstractionCode0
Relational recurrent neural networksCode0
Anticipating Technical Expertise and Capability Evolution in Research Communities using Dynamic Graph TransformersCode0
Double Equivariance for Inductive Link Prediction for Both New Nodes and New Relation TypesCode0
OCRT: Boosting Foundation Models in the Open World with Object-Concept-Relation TriadCode0
Modeling Content and Context with Deep Relational LearningCode0
Modularized Zero-shot VQA with Pre-trained ModelsCode0
MDE: Multiple Distance Embeddings for Link Prediction in Knowledge GraphsCode0
Robust Face Tracking using Multiple Appearance Models and Graph Relational LearningCode0
Meta Relational Learning for Few-Shot Link Prediction in Knowledge GraphsCode0
A Comparative Study of Distributional and Symbolic Paradigms for Relational LearningCode0
Logic Tensor Networks for Semantic Image InterpretationCode0
Mandolin: A Knowledge Discovery Framework for the Web of DataCode0
Differentially Private Relational Learning with Entity-level Privacy GuaranteesCode0
Lifted Relational Neural NetworksCode0
Leveraging Relational Information for Learning Weakly Disentangled RepresentationsCode0
Associative TransformerCode0
Lifted Inference beyond First-Order LogicCode0
LightPath: Lightweight and Scalable Path Representation LearningCode0
Mapping Natural Language Commands to Web ElementsCode0
One-Shot Relational Learning for Knowledge GraphsCode0
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