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 101–110 of 483 papers

TitleStatusHype
Benchmarking Systematic Relational Reasoning with Large Language and Reasoning Models—0
A Concept-Centered Hypertext Approach to Case-Based Retrieval—0
Efficient Inference and Learning in a Large Knowledge Base: Reasoning with Extracted Information using a Locally Groundable First-Order Probabilistic Logic—0
Deep Learning for Ontology Reasoning—0
Deep Inductive Logic Reasoning for Multi-Hop Reading Comprehension—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
Analysis of Nuanced Stances and Sentiment Towards Entities of US Politicians through the Lens of Moral Foundation Theory—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified