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 81–90 of 483 papers

TitleStatusHype
Computer-aided Tuberculosis Diagnosis with Attribute Reasoning AssistanceCode1
Fusing Context Into Knowledge Graph for Commonsense Question AnsweringCode1
LightPath: Lightweight and Scalable Path Representation LearningCode0
Lifted Inference beyond First-Order LogicCode0
Anticipating Technical Expertise and Capability Evolution in Research Communities using Dynamic Graph TransformersCode0
Leveraging Relational Information for Learning Weakly Disentangled RepresentationsCode0
Logic Tensor Networks for Semantic Image InterpretationCode0
Bridging Generative and Discriminative Learning: Few-Shot Relation Extraction via Two-Stage Knowledge-Guided Pre-trainingCode0
Breakpoint Transformers for Modeling and Tracking Intermediate BeliefsCode0
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