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 401–425 of 483 papers

TitleStatusHype
Visual Reasoning in Object-Centric Deep Neural Networks: A Comparative Cognition ApproachCode0
Large Class Separation is not what you need for Relational Reasoning-based OOD DetectionCode0
Language-Conditioned Graph Networks for Relational ReasoningCode0
Mandolin: A Knowledge Discovery Framework for the Web of DataCode0
Mapping Natural Language Commands to Web ElementsCode0
Cognitive Knowledge Graph Reasoning for One-shot Relational LearningCode0
MDE: Multiple Distance Embeddings for Link Prediction in Knowledge GraphsCode0
Bridging Generative and Discriminative Learning: Few-Shot Relation Extraction via Two-Stage Knowledge-Guided Pre-trainingCode0
Meta Relational Learning for Few-Shot Link Prediction in Knowledge GraphsCode0
Relational Learning for Joint Head and Human DetectionCode0
Breakpoint Transformers for Modeling and Tracking Intermediate BeliefsCode0
Beyond the Doors of Perception: Vision Transformers Represent Relations Between ObjectsCode0
Few-shot Knowledge Graph Relational Reasoning via Subgraph AdaptationCode0
Generalization of CNNs on Relational Reasoning with Bar ChartsCode0
Knowledge Graph Completion via Complex Tensor FactorizationCode0
Modeling Content and Context with Deep Relational LearningCode0
Benchmarking and Understanding Compositional Relational Reasoning of LLMsCode0
Unraveling the geometry of visual relational reasoningCode0
Explaining Local, Global, And Higher-Order Interactions In Deep LearningCode0
Modularized Zero-shot VQA with Pre-trained ModelsCode0
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
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified