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 251–275 of 712 papers

TitleStatusHype
Unbiased Video Scene Graph Generation via Visual and Semantic Dual Debiasing—0
KnowZRel: Common Sense Knowledge-based Zero-Shot Relationship Retrieval for Generalised Scene Graph GenerationCode0
FragFM: Hierarchical Framework for Efficient Molecule Generation via Fragment-Level Discrete Flow Matching—0
Agentic Medical Knowledge Graphs Enhance Medical Question Answering: Bridging the Gap Between LLMs and Evolving Medical Knowledge—0
Private Synthetic Graph Generation and Fused Gromov-Wasserstein Distance—0
Beyond Pairwise: Global Zero-shot Temporal Graph Generation—0
Leveraging V2X for Collaborative HD Maps Construction Using Scene Graph Generation—0
Flatten Graphs as Sequences: Transformers are Scalable Graph Generators—0
Do Graph Diffusion Models Accurately Capture and Generate Substructure Distributions?—0
Towards Fast Graph Generation via Autoregressive Noisy Filtration ModelingCode0
Evolving Hard Maximum Cut Instances for Quantum Approximate Optimization Algorithms—0
UniQ: Unified Decoder with Task-specific Queries for Efficient Scene Graph Generation—0
Graph Generative Pre-trained Transformer—0
Navigating the Unseen: Zero-shot Scene Graph Generation via Capsule-Based Equivariant Features—0
GraphMimic: Graph-to-Graphs Generative Modeling from Videos for Policy Learning—0
Hybrid Reciprocal Transformer with Triplet Feature Alignment for Scene Graph Generation—0
Learning 4D Panoptic Scene Graph Generation from Rich 2D Visual Scene—0
Relation-aware Hierarchical Prompt for Open-vocabulary Scene Graph Generation—0
KG4Diagnosis: A Hierarchical Multi-Agent LLM Framework with Knowledge Graph Enhancement for Medical Diagnosis—0
Training-free Heterogeneous Graph Condensation via Data SelectionCode0
A Deep Probabilistic Framework for Continuous Time Dynamic Graph GenerationCode0
AnalogXpert: Automating Analog Topology Synthesis by Incorporating Circuit Design Expertise into Large Language Models—0
SceneLLM: Implicit Language Reasoning in LLM for Dynamic Scene Graph Generation—0
Multi-Class and Multi-Task Strategies for Neural Directed Link PredictionCode0
Efficient Dynamic Attributed Graph Generation—0
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Benchmark Results

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