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 461–470 of 483 papers

TitleStatusHype
RuDaS: Synthetic Datasets for Rule Learning and Evaluation ToolsCode0
Principled and Efficient Motif Finding for Structure Learning of Lifted Graphical ModelsCode0
Privately Learning from Graphs with Applications in Fine-tuning Large Language ModelsCode0
Probing Cross-Modal Representations in Multi-Step Relational ReasoningCode0
Compositional Language Understanding with Text-based Relational ReasoningCode0
Propagation on Multi-relational Graphs for Node RegressionCode0
Propositionalization and Embeddings: Two Sides of the Same CoinCode0
Identifying Morality Frames in Political Tweets using Relational LearningCode0
An Explicitly Relational Neural Network ArchitectureCode0
Holographic Embeddings of Knowledge GraphsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified