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 301–310 of 483 papers

TitleStatusHype
Visual-Linguistic Agent: Towards Collaborative Contextual Object Reasoning—0
V-STaR: Benchmarking Video-LLMs on Video Spatio-Temporal Reasoning—0
Weakly Supervised Tweet Stance Classification by Relational Bootstrapping—0
Weighted First Order Model Counting with Directed Acyclic Graph Axioms—0
Working Memory Networks: Augmenting Memory Networks with a Relational Reasoning Module—0
SrTR: Self-reasoning Transformer with Visual-linguistic Knowledge for Scene Graph Generation—0
MIRAGE: A Multi-modal Benchmark for Spatial Perception, Reasoning, and Intelligence—0
Relational reasoning and inductive bias in transformers trained on a transitive inference task—0
LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs—0
3D Part Assembly Generation with Instance Encoded Transformer—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified