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

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Showing 31–40 of 483 papers

TitleStatusHype
DualVGR: A Dual-Visual Graph Reasoning Unit for Video Question AnsweringCode1
Compensating Supervision Incompleteness with Prior Knowledge in Semantic Image InterpretationCode1
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from TextCode1
BayReL: Bayesian Relational Learning for Multi-omics Data IntegrationCode1
Computer-aided Tuberculosis Diagnosis with Attribute Reasoning AssistanceCode1
Conditional Graph Information Bottleneck for Molecular Relational LearningCode1
Cross-Modal Causal Relational Reasoning for Event-Level Visual Question AnsweringCode1
DARER: Dual-task Temporal Relational Recurrent Reasoning Network for Joint Dialog Sentiment Classification and Act RecognitionCode1
Beyond Graph Neural Networks with Lifted Relational Neural NetworksCode1
COMPOSER: Compositional Reasoning of Group Activity in Videos with Keypoint-Only ModalityCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified