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 21–30 of 483 papers

TitleStatusHype
Enhancing the Utility of Higher-Order Information in Relational LearningCode1
Representational Alignment with Chemical Induced Fit for Molecular Relational Learning—0
Graph-Aware Isomorphic Attention for Adaptive Dynamics in TransformersCode2
Reasoning-Oriented and Analogy-Based Methods for Locating and Editing in Zero-Shot Event-Relational Reasoning—0
Path-of-Thoughts: Extracting and Following Paths for Robust Relational Reasoning with Large Language Models—0
Explicit Relational Reasoning Network for Scene Text Detection—0
Benchmarking and Understanding Compositional Relational Reasoning of LLMsCode0
3D Interaction Geometric Pre-training for Molecular Relational LearningCode1
Text-Guided Coarse-to-Fine Fusion Network for Robust Remote Sensing Visual Question Answering—0
Financial Risk Assessment via Long-term Payment Behavior Sequence Folding—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified