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 101–125 of 483 papers

TitleStatusHype
Deep Semantic Abstractions of Everyday Human Activities: On Commonsense Representations of Human Interactions—0
Deep reinforcement learning with relational inductive biases—0
Benchmarking Systematic Relational Reasoning with Large Language and Reasoning Models—0
A Concept-Centered Hypertext Approach to Case-Based Retrieval—0
Explicit Relational Reasoning Network for Scene Text Detection—0
Deep Sets for Generalization in RL—0
Demystifying Relational Latent Representations—0
Desk Organization: Effect of Multimodal Inputs on Spatial Relational Learning—0
DEVICE: DEpth and VIsual ConcEpts Aware Transformer for TextCaps—0
Differentiable Parsing and Visual Grounding of Natural Language Instructions for Object Placement—0
Deep Learning for Ontology Reasoning—0
Deep Inductive Logic Reasoning for Multi-Hop Reading Comprehension—0
Boosting Neural Language Inference via Cascaded Interactive Reasoning—0
Distilling Structured Knowledge for Text-Based Relational Reasoning—0
Analysis of Nuanced Stances and Sentiment Towards Entities of US Politicians through the Lens of Moral Foundation Theory—0
A Novel Neural-symbolic System under Statistical Relational Learning—0
Does Entity Abstraction Help Generative Transformers Reason?—0
Domain Adaptive Relational Reasoning for 3D Multi-Organ Segmentation—0
Domain-Liftability of Relational Marginal Polytopes—0
Broadcasting Convolutional Network for Visual Relational Reasoning—0
Deep Generative Models for Ultra-High Granularity Particle Physics Detector Simulation: A Voyage From Emulation to Extrapolation—0
Decoupling Mixture-of-Graphs: Unseen Relational Learning for Knowledge Graph Completion by Fusing Ontology and Textual Experts—0
A Complete Characterization of Projectivity for Statistical Relational Models—0
Effective Learning of Probabilistic Models for Clinical Predictions from Longitudinal Data—0
Battery GraphNets : Relational Learning for Lithium-ion Batteries(LiBs) Life Estimation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified