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 271–280 of 483 papers

TitleStatusHype
RelEx: A Model-Agnostic Relational Model Explainer—0
Hyperbolic Manifold Regression—0
Domain Adaptive Relational Reasoning for 3D Multi-Organ Segmentation—0
Reasoning with Latent Structure Refinement for Document-Level Relation ExtractionCode1
Sampling Community Structure—0
Neural-Symbolic Relational Reasoning on Graph Models: Effective Link Inference and Computation from Knowledge Bases—0
Construction and Elicitation of a Black Box Model in the Game of Bridge—0
Scalable Multi-Hop Relational Reasoning for Knowledge-Aware Question AnsweringCode1
Machine Number Sense: A Dataset of Visual Arithmetic Problems for Abstract and Relational ReasoningCode1
A Complete Characterization of Projectivity for Statistical Relational Models—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified