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 201–225 of 483 papers

TitleStatusHype
Agent-Centric Representations for Multi-Agent Reinforcement Learning—0
Extrapolatable Relational Reasoning With Comparators in Low-Dimensional Manifolds—0
Deep Inductive Logic Reasoning for Multi-Hop Reading Comprehension—0
Analysis of Nuanced Stances and Sentiment Towards Entities of US Politicians through the Lens of Moral Foundation Theory—0
Interactive Autonomous Navigation with Internal State Inference and Interactivity Estimation—0
Deep Learning for Ontology Reasoning—0
Interpretable Reinforcement Learning With Neural Symbolic Logic—0
Introducing DRAIL -- a Step Towards Declarative Deep Relational Learning—0
FreeQ-Graph: Free-form Querying with Semantic Consistent Scene Graph for 3D Scene Understanding—0
A Semantic Matching Energy Function for Learning with Multi-relational Data—0
Learning Relational Features with Backward Random Walks—0
Jointly Extracting Explicit and Implicit Relational Triples with Reasoning Pattern Enhanced Binary Pointer Network—0
Joint Modeling of Visual Objects and Relations for Scene Graph Generation—0
KeLP at SemEval-2017 Task 3: Learning Pairwise Patterns in Community Question Answering—0
kLog: A Language for Logical and Relational Learning with Kernels—0
kLogNLP: Graph Kernel--based Relational Learning of Natural Language—0
Desk Organization: Effect of Multimodal Inputs on Spatial Relational Learning—0
Knowledge-augmented Graph Neural Networks with Concept-aware Attention for Adverse Drug Event Detection—0
A Boosting Approach to Learning Graph Representations—0
Knowledge Graph Embedding via Graph Attenuated Attention Networks—0
Structured Knowledge Grounding for Question Answering—0
Look Around for Anomalies: Weakly-Supervised Anomaly Detection via Context-Motion Relational Learning—0
Learning Probabilistic Logic Programs in Continuous Domains—0
Finding ReMO (Related Memory Object): A Simple Neural Architecture for Text based Reasoning—0
Financial Risk Assessment via Long-term Payment Behavior Sequence Folding—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified