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 511–520 of 712 papers

TitleStatusHype
Scalable Deep Generative Modeling for Sparse Graphs—0
Scalable Regularization of Scene Graph Generation Models using Symbolic Theories—0
Counterfactual Critic Multi-Agent Training for Scene Graph Generation—0
Scene Graph Generation: A Comprehensive Survey—0
Scene Graph Generation for Better Image Captioning?—0
Scene Graph Generation Strategy with Co-occurrence Knowledge and Learnable Term Frequency—0
Scene Graph Generation via Conditional Random Fields—0
Scene Graph Generation with External Knowledge and Image Reconstruction—0
Scene Graph Generation with Geometric Context—0
SceneLLM: Implicit Language Reasoning in LLM for Dynamic Scene Graph Generation—0
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Benchmark Results

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