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
Lifted Inference beyond First-Order LogicCode0
RLIPv2: Fast Scaling of Relational Language-Image Pre-trainingCode1
Learning the meanings of function words from grounded language using a visual question answering modelCode0
CommonsenseVIS: Visualizing and Understanding Commonsense Reasoning Capabilities of Natural Language Models—0
LightPath: Lightweight and Scalable Path Representation LearningCode0
Anticipating Technical Expertise and Capability Evolution in Research Communities using Dynamic Graph TransformersCode0
A Multi-Task Perspective for Link Prediction with New Relation Types and Nodes—0
Large Class Separation is not what you need for Relational Reasoning-based OOD DetectionCode0
From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of ThoughtCode2
Statistical relational learning and neuro-symbolic AI: what does first-order logic offer?—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified