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 51–75 of 483 papers

TitleStatusHype
Reasoning with Latent Structure Refinement for Document-Level Relation ExtractionCode1
Beyond Graph Neural Networks with Lifted Relational Neural NetworksCode1
Redundancy-Free Self-Supervised Relational Learning for Graph ClusteringCode1
Relational Context Learning for Human-Object Interaction DetectionCode1
3D Interaction Geometric Pre-training for Molecular Relational LearningCode1
Relational VAE: A Continuous Latent Variable Model for Graph Structured DataCode1
RLIPv2: Fast Scaling of Relational Language-Image Pre-trainingCode1
RRNet: Relational Reasoning Network with Parallel Multi-scale Attention for Salient Object Detection in Optical Remote Sensing ImagesCode1
Scale-Localized Abstract ReasoningCode1
Self-Attentive Associative MemoryCode1
Self-Supervised Time Series Representation Learning by Inter-Intra Relational ReasoningCode1
Semantic Novelty Detection via Relational ReasoningCode1
DARER: Dual-task Temporal Relational Recurrent Reasoning Network for Joint Dialog Sentiment Classification and Act RecognitionCode1
Deep Relational Reasoning Graph Network for Arbitrary Shape Text DetectionCode1
CORE-Text: Improving Scene Text Detection with Contrastive Relational ReasoningCode1
COMPOSER: Compositional Reasoning of Group Activity in Videos with Keypoint-Only ModalityCode1
Cross-Modal Causal Relational Reasoning for Event-Level Visual Question AnsweringCode1
Dynamic-Group-Aware Networks for Multi-Agent Trajectory Prediction with Relational ReasoningCode1
Enhancing the Utility of Higher-Order Information in Relational LearningCode1
ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive LearningCode1
Computer-aided Tuberculosis Diagnosis with Attribute Reasoning AssistanceCode1
DualVGR: A Dual-Visual Graph Reasoning Unit for Video Question AnsweringCode1
Compensating Supervision Incompleteness with Prior Knowledge in Semantic Image InterpretationCode1
Generative 3D Part Assembly via Dynamic Graph LearningCode1
Few-shot Relational Reasoning via Connection Subgraph PretrainingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified