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 241–250 of 483 papers

TitleStatusHype
Distributed Associative Memory Network with Association Reinforcing Loss—0
Does Entity Abstraction Help Generative Transformers Reason?—0
Domain Adaptive Relational Reasoning for 3D Multi-Organ Segmentation—0
Ranking relations using analogies in biological and information networks—0
Reading The Web with Learned Syntactic-Semantic Inference Rules—0
Reasoning Graph Networks for Kinship Verification: from Star-shaped to Hierarchical—0
Reasoning-Oriented and Analogy-Based Methods for Locating and Editing in Zero-Shot Event-Relational Reasoning—0
Recent Advances in Heterogeneous Relation Learning for Recommendation—0
Recurrent Relational Memory Network for Unsupervised Image Captioning—0
Recursive Neural Networks Can Learn Logical Semantics—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified