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 76–100 of 483 papers

TitleStatusHype
COMPOSER: Compositional Reasoning of Group Activity in Videos with Keypoint-Only ModalityCode1
Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph RepresentationsCode1
Relational inductive biases, deep learning, and graph networksCode1
Video Dialog as Conversation about Objects Living in Space-TimeCode1
Generative Adversarial Zero-Shot Relational Learning for Knowledge GraphsCode1
Computer-aided Tuberculosis Diagnosis with Attribute Reasoning AssistanceCode1
GroupNet: Multiscale Hypergraph Neural Networks for Trajectory Prediction with Relational ReasoningCode1
Meta Relational Learning for Few-Shot Link Prediction in Knowledge GraphsCode0
Modeling Content and Context with Deep Relational LearningCode0
Mapping Natural Language Commands to Web ElementsCode0
Anticipating Technical Expertise and Capability Evolution in Research Communities using Dynamic Graph TransformersCode0
MDE: Multiple Distance Embeddings for Link Prediction in Knowledge GraphsCode0
Modularized Zero-shot VQA with Pre-trained ModelsCode0
Bridging Generative and Discriminative Learning: Few-Shot Relation Extraction via Two-Stage Knowledge-Guided Pre-trainingCode0
Breakpoint Transformers for Modeling and Tracking Intermediate BeliefsCode0
Logic Tensor Networks for Semantic Image InterpretationCode0
Mandolin: A Knowledge Discovery Framework for the Web of DataCode0
An Insect-Inspired Randomly, Weighted Neural Network with Random Fourier Features For Neuro-Symbolic Relational LearningCode0
Beyond the Doors of Perception: Vision Transformers Represent Relations Between ObjectsCode0
Lifted Relational Neural NetworksCode0
An Explicitly Relational Neural Network ArchitectureCode0
Lifted Inference beyond First-Order LogicCode0
LightPath: Lightweight and Scalable Path Representation LearningCode0
Benchmarking and Understanding Compositional Relational Reasoning of LLMsCode0
Learning the meanings of function words from grounded language using a visual question answering modelCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified