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 -
Latest papers
Visual Reasoning in Object-Centric Deep Neural Networks: A Comparative Cognition Approach
GuillermoPuebla/object-centric-reasoning
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To this end, these models use several kinds of attention mechanisms to segregate the individual objects in a scene from the background and from other objects.
FGeo-HyperGNet: Geometric Problem Solving Integrating Formal Symbolic System and Hypergraph Neural Network
The symbolic part is a formal system built on FormalGeo, which can automatically perform geomertic relational reasoning and algebraic calculations and organize the solving process into a solution hypertree with conditions as hypernodes and theorems as hyperedges.
Pix2Code: Learning to Compose Neural Visual Concepts as Programs
The challenge in learning abstract concepts from images in an unsupervised fashion lies in the required integration of visual perception and generalizable relational reasoning.
MolTC: Towards Molecular Relational Modeling In Language Models
Molecular Relational Learning (MRL), aiming to understand interactions between molecular pairs, plays a pivotal role in advancing biochemical research.
zrLLM: Zero-Shot Relational Learning on Temporal Knowledge Graphs with Large Language Models
zifengding/zrllm
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We first input the text descriptions of KG relations into large language models (LLMs) for generating relation representations, and then introduce them into embedding-based TKGF methods.
When can transformers reason with abstract symbols?
eboix/relational-reasoning
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We investigate the capabilities of transformer models on relational reasoning tasks.
Associative Transformer
yuweisunn/associative-transformer
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Existing studies such as the Coordination method employ iterative cross-attention mechanisms with a bottleneck to enable the sparse association of inputs.
Redundancy-Free Self-Supervised Relational Learning for Graph Clustering
yisiyu95/r2fgc
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Graph clustering, which learns the node representations for effective cluster assignments, is a fundamental yet challenging task in data analysis and has received considerable attention accompanied by graph neural networks in recent years.
Reconstructing Groups of People with Hypergraph Relational Reasoning
boycehbz/GroupRec
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ICCV 2023
To address the obstacles, we fully exploit crowd features for reconstructing groups of people from a monocular image.
RLIPv2: Fast Scaling of Relational Language-Image Pre-training
jacobyuan7/rlipv2
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ICCV 2023
In this paper, we propose RLIPv2, a fast converging model that enables the scaling of relational pre-training to large-scale pseudo-labelled scene graph data.
