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 76–100 of 483 papers

TitleStatusHype
COMPOSER: Compositional Reasoning of Group Activity in Videos with Keypoint-Only ModalityCode1
RLIPv2: Fast Scaling of Relational Language-Image Pre-trainingCode1
Relational Learning with Gated and Attentive Neighbor Aggregator for Few-Shot Knowledge Graph CompletionCode1
Visual Abstract Thinking Empowers Multimodal ReasoningCode1
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
Modeling Content and Context with Deep Relational LearningCode0
Modularized Zero-shot VQA with Pre-trained ModelsCode0
MDE: Multiple Distance Embeddings for Link Prediction in Knowledge GraphsCode0
Anticipating Technical Expertise and Capability Evolution in Research Communities using Dynamic Graph TransformersCode0
Meta Relational Learning for Few-Shot Link Prediction in Knowledge GraphsCode0
Bridging Generative and Discriminative Learning: Few-Shot Relation Extraction via Two-Stage Knowledge-Guided Pre-trainingCode0
Mandolin: A Knowledge Discovery Framework for the Web of DataCode0
Breakpoint Transformers for Modeling and Tracking Intermediate BeliefsCode0
Mapping Natural Language Commands to Web ElementsCode0
MUREL: Multimodal Relational Reasoning for Visual Question AnsweringCode0
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
LightPath: Lightweight and Scalable Path Representation LearningCode0
An Explicitly Relational Neural Network ArchitectureCode0
Lifted Inference beyond First-Order LogicCode0
Benchmarking and Understanding Compositional Relational Reasoning of LLMsCode0
Learning the meanings of function words from grounded language using a visual question answering modelCode0
Large Class Separation is not what you need for Relational Reasoning-based OOD DetectionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified