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

Showing 101–110 of 483 papers

TitleStatusHype
Unraveling the geometry of visual relational reasoningCode0
Representational Alignment with Chemical Induced Fit for Molecular Relational Learning—0
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
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
Visual-Linguistic Agent: Towards Collaborative Contextual Object Reasoning—0
RESOLVE: Relational Reasoning with Symbolic and Object-Level Features Using Vector Symbolic ProcessingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified