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 91–100 of 483 papers

TitleStatusHype
Mapping Natural Language Commands to Web ElementsCode0
MUREL: Multimodal Relational Reasoning for Visual Question AnsweringCode0
An Insect-Inspired Randomly, Weighted Neural Network with Random Fourier Features For Neuro-Symbolic Relational LearningCode0
Beyond the Doors of Perception: Vision Transformers Represent Relations Between ObjectsCode0
LightPath: Lightweight and Scalable Path Representation LearningCode0
An Explicitly Relational Neural Network ArchitectureCode0
Lifted Inference beyond First-Order LogicCode0
Benchmarking and Understanding Compositional Relational Reasoning of LLMsCode0
Learning the meanings of function words from grounded language using a visual question answering modelCode0
Large Class Separation is not what you need for Relational Reasoning-based OOD DetectionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified