data/graph.json

{
 "spatial-rag": [
  "cg-rag",
  "grag",
  "polyhedronnet",
  "rag-without-forgetting",
  "spatial-agent"
 ],
 "grag": [
  "cg-rag",
  "rag-without-forgetting",
  "spatial-rag",
  "taga",
  "transferable-deep-clustering"
 ],
 "cg-rag": [
  "grag",
  "rag-without-forgetting",
  "spatial-rag",
  "taga"
 ],
 "rag-without-forgetting": [
  "cg-rag",
  "grag",
  "spatial-rag",
  "taga"
 ],
 "spatial-agent": [
  "skillops",
  "spatial-rag"
 ],
 "domain-specialization-survey": [
  "influence-maximization",
  "propagation-trees",
  "resource-efficient-llm-survey",
  "source-localization-vae",
  "temporal-domain-generalization",
  "uq-icl"
 ],
 "gnn-book": [
  "bridging-spatial-spectral",
  "deep-graph-translation",
  "generative-graph-survey",
  "graphnarrator",
  "healthcare-kg-review",
  "heterogeneous-temporal-gnn",
  "implicit-gnn-transformation",
  "influence-maximization",
  "spectral-temporal-gnn",
  "staleness-distributed-gnn",
  "taga"
 ],
 "transferable-deep-clustering": [
  "grag",
  "taga"
 ],
 "taga": [
  "bridging-spatial-spectral",
  "cg-rag",
  "deep-graph-translation",
  "gnn-book",
  "grag",
  "graphnarrator",
  "heterogeneous-temporal-gnn",
  "implicit-gnn-transformation",
  "influence-maximization",
  "key-player-underground-forums",
  "polyhedronnet",
  "rag-without-forgetting",
  "spectral-temporal-gnn",
  "staleness-distributed-gnn",
  "transferable-deep-clustering"
 ],
 "graphnarrator": [
  "bridging-spatial-spectral",
  "deep-graph-translation",
  "gnn-book",
  "heterogeneous-temporal-gnn",
  "implicit-gnn-transformation",
  "influence-maximization",
  "interpretable-deep-graph-generation",
  "molworld",
  "spectral-temporal-gnn",
  "staleness-distributed-gnn",
  "taga"
 ],
 "latentexplainer": [
  "interpretable-deep-graph-generation"
 ],
 "polyhedronnet": [
  "key-player-underground-forums",
  "spatial-rag",
  "taga"
 ],
 "fedspallm": [
  "fedat",
  "resource-efficient-llm-survey",
  "staleness-distributed-gnn",
  "temporal-domain-generalization"
 ],
 "saliency-bench": [],
 "propagation-trees": [
  "domain-specialization-survey",
  "influence-maximization",
  "lumina-grid",
  "misinformation-twitter",
  "resource-efficient-llm-survey",
  "source-localization-vae",
  "spectral-temporal-gnn",
  "temporal-domain-generalization",
  "uq-icl",
  "world-models-epidemiology"
 ],
 "continuous-domain-generalization": [
  "temporal-domain-generalization"
 ],
 "healthcare-kg-review": [
  "bridging-spatial-spectral",
  "covid-spatiotemporal",
  "generative-graph-survey",
  "gnn-book"
 ],
 "embers": [
  "covid-spatiotemporal",
  "event-prediction-survey",
  "misinformation-twitter",
  "multitask-spatiotemporal-forecasting",
  "world-models-epidemiology"
 ],
 "influence-maximization": [
  "admm-deep-learning",
  "bridging-spatial-spectral",
  "deep-graph-translation",
  "domain-specialization-survey",
  "explanation-guided-learning-survey",
  "gnn-book",
  "graphnarrator",
  "heterogeneous-temporal-gnn",
  "implicit-gnn-transformation",
  "propagation-trees",
  "resource-efficient-llm-survey",
  "source-localization-vae",
  "spectral-temporal-gnn",
  "staleness-distributed-gnn",
  "taga",
  "temporal-domain-generalization",
  "uq-icl"
 ],
 "generative-graph-survey": [
  "bridging-spatial-spectral",
  "deep-graph-translation",
  "gnn-book",
  "healthcare-kg-review",
  "implicit-gnn-transformation",
  "interpretable-deep-graph-generation",
  "source-localization-vae"
 ],
 "event-prediction-survey": [
  "covid-spatiotemporal",
  "embers",
  "multitask-spatiotemporal-forecasting"
 ],
 "resource-efficient-llm-survey": [
  "domain-specialization-survey",
  "fedat",
  "fedspallm",
  "influence-maximization",
  "propagation-trees",
  "source-localization-vae",
  "staleness-distributed-gnn",
  "temporal-domain-generalization",
  "uq-icl"
 ],
 "uq-icl": [
  "domain-specialization-survey",
  "influence-maximization",
  "propagation-trees",
  "resource-efficient-llm-survey",
  "source-localization-vae",
  "temporal-domain-generalization"
 ],
 "staleness-distributed-gnn": [
  "bridging-spatial-spectral",
  "deep-graph-translation",
  "fedat",
  "fedspallm",
  "gnn-book",
  "graphnarrator",
  "heterogeneous-temporal-gnn",
  "implicit-gnn-transformation",
  "influence-maximization",
  "resource-efficient-llm-survey",
  "spectral-temporal-gnn",
  "taga",
  "temporal-domain-generalization"
 ],
 "spectral-temporal-gnn": [
  "bridging-spatial-spectral",
  "deep-graph-translation",
  "gnn-book",
  "graphnarrator",
  "heterogeneous-temporal-gnn",
  "implicit-gnn-transformation",
  "influence-maximization",
  "propagation-trees",
  "sst-mamba-transformer",
  "staleness-distributed-gnn",
  "taga"
 ],
 "bridging-spatial-spectral": [
  "deep-graph-translation",
  "generative-graph-survey",
  "gnn-book",
  "graphnarrator",
  "healthcare-kg-review",
  "heterogeneous-temporal-gnn",
  "implicit-gnn-transformation",
  "influence-maximization",
  "spectral-temporal-gnn",
  "staleness-distributed-gnn",
  "taga"
 ],
 "admm-deep-learning": [
  "influence-maximization"
 ],
 "implicit-gnn-transformation": [
  "bridging-spatial-spectral",
  "deep-graph-translation",
  "generative-graph-survey",
  "gnn-book",
  "graphnarrator",
  "heterogeneous-temporal-gnn",
  "influence-maximization",
  "interpretable-deep-graph-generation",
  "source-localization-vae",
  "spectral-temporal-gnn",
  "staleness-distributed-gnn",
  "taga"
 ],
 "sst-mamba-transformer": [
  "spectral-temporal-gnn"
 ],
 "fedat": [
  "fedspallm",
  "resource-efficient-llm-survey",
  "staleness-distributed-gnn"
 ],
 "misinformation-twitter": [
  "covid-spatiotemporal",
  "embers",
  "propagation-trees",
  "world-models-epidemiology"
 ],
 "multitask-spatiotemporal-forecasting": [
  "covid-spatiotemporal",
  "embers",
  "event-prediction-survey"
 ],
 "covid-spatiotemporal": [
  "embers",
  "event-prediction-survey",
  "healthcare-kg-review",
  "misinformation-twitter",
  "multitask-spatiotemporal-forecasting",
  "world-models-epidemiology"
 ],
 "heterogeneous-temporal-gnn": [
  "bridging-spatial-spectral",
  "deep-graph-translation",
  "gnn-book",
  "graphnarrator",
  "implicit-gnn-transformation",
  "influence-maximization",
  "key-player-underground-forums",
  "spectral-temporal-gnn",
  "staleness-distributed-gnn",
  "taga"
 ],
 "explanation-guided-learning-survey": [
  "influence-maximization",
  "source-localization-vae"
 ],
 "deep-graph-translation": [
  "bridging-spatial-spectral",
  "generative-graph-survey",
  "gnn-book",
  "graphnarrator",
  "heterogeneous-temporal-gnn",
  "implicit-gnn-transformation",
  "influence-maximization",
  "interpretable-deep-graph-generation",
  "source-localization-vae",
  "spectral-temporal-gnn",
  "staleness-distributed-gnn",
  "taga"
 ],
 "interpretable-deep-graph-generation": [
  "deep-graph-translation",
  "generative-graph-survey",
  "graphnarrator",
  "implicit-gnn-transformation",
  "latentexplainer",
  "source-localization-vae"
 ],
 "source-localization-vae": [
  "deep-graph-translation",
  "domain-specialization-survey",
  "explanation-guided-learning-survey",
  "generative-graph-survey",
  "implicit-gnn-transformation",
  "influence-maximization",
  "interpretable-deep-graph-generation",
  "propagation-trees",
  "resource-efficient-llm-survey",
  "temporal-domain-generalization",
  "uq-icl"
 ],
 "temporal-domain-generalization": [
  "continuous-domain-generalization",
  "domain-specialization-survey",
  "fedspallm",
  "influence-maximization",
  "propagation-trees",
  "resource-efficient-llm-survey",
  "source-localization-vae",
  "staleness-distributed-gnn",
  "uq-icl"
 ],
 "key-player-underground-forums": [
  "heterogeneous-temporal-gnn",
  "polyhedronnet",
  "taga"
 ],
 "world-models-epidemiology": [
  "covid-spatiotemporal",
  "embers",
  "lumina-grid",
  "misinformation-twitter",
  "molworld",
  "propagation-trees"
 ],
 "molworld": [
  "graphnarrator",
  "world-models-epidemiology"
 ],
 "lumina-grid": [
  "propagation-trees",
  "world-models-epidemiology"
 ],
 "skillops": [
  "spatial-agent"
 ]
}