SOTAVerified

Graph Generation

Graph Generation is an important research area with significant applications in drug and material designs.

Source: Graph Deconvolutional Generation

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 681–690 of 712 papers

TitleStatusHype
R2RML and RML Comparison for RDF Generation, their Rules Validation and Inconsistency Resolution—0
Random Walk Diffusion for Efficient Large-Scale Graph Generation—0
RealGraph: A Multiview Dataset for 4D Real-world Context Graph Generation—0
Realistic molecule optimization on a learned graph manifold—0
ReCon1M:A Large-scale Benchmark Dataset for Relation Comprehension in Remote Sensing Imagery—0
Reinforcement Learning Enhanced Explainer for Graph Neural Networks—0
Relation-aware Hierarchical Prompt for Open-vocabulary Scene Graph Generation—0
Relation-R1: Cognitive Chain-of-Thought Guided Reinforcement Learning for Unified Relational Comprehension—0
Relation Regularized Scene Graph Generation—0
Representing Time-Continuous Behavior of Cyber-Physical Systems in Knowledge Graphs—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RNNStreetMover0.03—Unverified
2GraphRNNStreetMover0.02—Unverified
3GGT without CAStreetMover0.02—Unverified
4GGTStreetMover0.02—Unverified