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 151–175 of 712 papers

TitleStatusHype
Beyond Visual Appearances: Privacy-sensitive Objects Identification via Hybrid Graph Reasoning—0
Input Conditioned Graph Generation for Language AgentsCode0
Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space—0
SkySenseGPT: A Fine-Grained Instruction Tuning Dataset and Model for Remote Sensing Vision-Language UnderstandingCode2
STAR: A First-Ever Dataset and A Large-Scale Benchmark for Scene Graph Generation in Large-Size Satellite ImageryCode2
Advancing Graph Generation through Beta DiffusionCode1
Large Language Models for Constrained-Based Causal DiscoveryCode1
Cometh: A continuous-time discrete-state graph diffusion model—0
ReCon1M:A Large-scale Benchmark Dataset for Relation Comprehension in Remote Sensing Imagery—0
Variational Flow Matching for Graph Generation—0
Combinatorial Complex Score-based Diffusion Modelling through Stochastic Differential EquationsCode1
Semantic Similarity Score for Measuring Visual Similarity at Semantic Level—0
Leveraging Predicate and Triplet Learning for Scene Graph GenerationCode1
CYCLO: Cyclic Graph Transformer Approach to Multi-Object Relationship Modeling in Aerial Videos—0
Improving global awareness of linkset predictions using Cross-Attentive Modulation tokens—0
Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion ModelsCode0
OED: Towards One-stage End-to-End Dynamic Scene Graph GenerationCode1
Exploring Edge Probability Graph Models Beyond Edge Independency: Concepts, Analyses, and Algorithms—0
REACT: Real-time Efficiency and Accuracy Compromise for Tradeoffs in Scene Graph GenerationCode2
Score-based Generative Models with Adaptive Momentum—0
MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation—0
Scene Graph Generation Strategy with Co-occurrence Knowledge and Learnable Term Frequency—0
Discrete-state Continuous-time Diffusion for Graph GenerationCode1
4D Panoptic Scene Graph GenerationCode3
Exploring the Individuality and Collectivity of Intents behind Interactions for Graph Collaborative FilteringCode1
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Benchmark Results

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