Relational Reasoning
149 papers with code • 1 benchmarks • 12 datasets
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.
Benchmarks
These leaderboards are used to track progress in Relational Reasoning
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Libraries
Use these libraries to find Relational Reasoning models and implementationsDatasets
WebKB
RAVEN
AbstractReasoning
PGM
PISC
SPARTQA -
Most implemented papers
Neural Logic Machines
google/neural-logic-machines
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ICLR 2019
We propose the Neural Logic Machine (NLM), a neural-symbolic architecture for both inductive learning and logic reasoning.
An Explicitly Relational Neural Network Architecture
giancarlok/relationaltasks
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ICML 2020
With a view to bridging the gap between deep learning and symbolic AI, we present a novel end-to-end neural network architecture that learns to form propositional representations with an explicitly relational structure from raw pixel data.
MDE: Multiple Distance Embeddings for Link Prediction in Knowledge Graphs
mlwin-de/MDE
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We propose the Multiple Distance Embedding model (MDE) that addresses these limitations and a framework to collaboratively combine variant latent distance-based terms.
Compensating Supervision Incompleteness with Prior Knowledge in Semantic Image Interpretation
ivanDonadello/Visual-Relationship-Detection-LTN
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This requires the detection of visual relationships: triples (subject, relation, object) describing a semantic relation between a subject and an object.
CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning
INK-USC/CommonGen
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Findings of the Association for Computational Linguistics 2020
In this paper, we present a constrained text generation task, CommonGen associated with a benchmark dataset, to explicitly test machines for the ability of generative commonsense reasoning.
Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs
Panda0406/Zero-shot-knowledge-graph-relational-learning
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Large-scale knowledge graphs (KGs) are shown to become more important in current information systems.
Deep Relational Reasoning Graph Network for Arbitrary Shape Text Detection
In this paper, we propose a novel unified relational reasoning graph network for arbitrary shape text detection.
Machine Number Sense: A Dataset of Visual Arithmetic Problems for Abstract and Relational Reasoning
zwh1999anne/Machine-Number-Sense-Dataset
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To endow such a crucial cognitive ability to machine intelligence, we propose a dataset, Machine Number Sense (MNS), consisting of visual arithmetic problems automatically generated using a grammar model--And-Or Graph (AOG).
Scalable Multi-Hop Relational Reasoning for Knowledge-Aware Question Answering
Existing work on augmenting question answering (QA) models with external knowledge (e. g., knowledge graphs) either struggle to model multi-hop relations efficiently, or lack transparency into the model's prediction rationale.
Reasoning with Latent Structure Refinement for Document-Level Relation Extraction
Document-level relation extraction requires integrating information within and across multiple sentences of a document and capturing complex interactions between inter-sentence entities.
