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queries/queries_nvidia-cosmos.jsonl
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| 1 |
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{"id": "nvidia-cosmos_T1_41", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Video Pretraining Corpus?", "ground_truth": ["Video Pretraining Corpus", "DATA"], "concept_id": 41, "hop_depth": 0}
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| 2 |
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{"id": "nvidia-cosmos_T1_8", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Synthetic Data Pipeline?", "ground_truth": ["Synthetic Data Pipeline", "PIPELINE"], "concept_id": 8, "hop_depth": 0}
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| 3 |
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{"id": "nvidia-cosmos_T1_2", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Cosmos-1.0-Predict?", "ground_truth": ["Cosmos-1.0-Predict", "MODEL"], "concept_id": 2, "hop_depth": 0}
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| 4 |
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{"id": "nvidia-cosmos_T1_18", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Isaac Lab Integration?", "ground_truth": ["Isaac Lab Integration", "INTEGRAT"], "concept_id": 18, "hop_depth": 0}
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| 5 |
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{"id": "nvidia-cosmos_T1_16", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is AV Scenario Simulation?", "ground_truth": ["AV Scenario Simulation", "PROCESS"], "concept_id": 16, "hop_depth": 0}
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| 6 |
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{"id": "nvidia-cosmos_T1_15", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Robot Policy Training?", "ground_truth": ["Robot Policy Training", "PROCESS"], "concept_id": 15, "hop_depth": 0}
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| 7 |
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{"id": "nvidia-cosmos_T1_9", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Sim-to-Real Transfer?", "ground_truth": ["Sim-to-Real Transfer", "CONCEPT"], "concept_id": 9, "hop_depth": 0}
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| 8 |
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{"id": "nvidia-cosmos_T1_7", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Physical AI?", "ground_truth": ["Physical AI", "CONCEPT"], "concept_id": 7, "hop_depth": 0}
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| 9 |
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{"id": "nvidia-cosmos_T1_35", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Teleoperation Data?", "ground_truth": ["Teleoperation Data", "DATA"], "concept_id": 35, "hop_depth": 0}
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| 10 |
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{"id": "nvidia-cosmos_T1_6", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Cosmos-1.0-Nano?", "ground_truth": ["Cosmos-1.0-Nano", "MODEL"], "concept_id": 6, "hop_depth": 0}
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| 11 |
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{"id": "nvidia-cosmos_T1_28", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Post-Training / Fine-Tuning?", "ground_truth": ["Post-Training / Fine-Tuning", "PROCESS"], "concept_id": 28, "hop_depth": 0}
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| 12 |
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{"id": "nvidia-cosmos_T1_3", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Cosmos-1.0-Transfer?", "ground_truth": ["Cosmos-1.0-Transfer", "MODEL"], "concept_id": 3, "hop_depth": 0}
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| 13 |
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{"id": "nvidia-cosmos_T1_44", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Robot Manipulation?", "ground_truth": ["Robot Manipulation", "CAPABILI"], "concept_id": 44, "hop_depth": 0}
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| 14 |
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{"id": "nvidia-cosmos_T1_37", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is NeMo Framework?", "ground_truth": ["NeMo Framework", "TOOL"], "concept_id": 37, "hop_depth": 0}
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| 15 |
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{"id": "nvidia-cosmos_T1_14", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Video-to-World Prediction?", "ground_truth": ["Video-to-World Prediction", "CAPABILI"], "concept_id": 14, "hop_depth": 0}
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| 16 |
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{"id": "nvidia-cosmos_T1_45", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is 3D Scene Generation?", "ground_truth": ["3D Scene Generation", "CAPABILI"], "concept_id": 45, "hop_depth": 0}
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| 17 |
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{"id": "nvidia-cosmos_T1_17", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Omniverse Integration?", "ground_truth": ["Omniverse Integration", "INTEGRAT"], "concept_id": 17, "hop_depth": 0}
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| 18 |
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{"id": "nvidia-cosmos_T1_20", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is GR00T Integration?", "ground_truth": ["GR00T Integration", "INTEGRAT"], "concept_id": 20, "hop_depth": 0}
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| 19 |
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{"id": "nvidia-cosmos_T1_1", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Cosmos World Foundation Model?", "ground_truth": ["Cosmos World Foundation Model", "PLATFORM"], "concept_id": 1, "hop_depth": 0}
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| 20 |
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{"id": "nvidia-cosmos_T1_43", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Domain Randomization?", "ground_truth": ["Domain Randomization", "TECHNIQU"], "concept_id": 43, "hop_depth": 0}
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| 21 |
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{"id": "nvidia-cosmos_T1_39", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Generative World Simulation?", "ground_truth": ["Generative World Simulation", "CONCEPT"], "concept_id": 39, "hop_depth": 0}
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| 22 |
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{"id": "nvidia-cosmos_T1_23", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Action Conditioning?", "ground_truth": ["Action Conditioning", "MECHANIS"], "concept_id": 23, "hop_depth": 0}
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| 23 |
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{"id": "nvidia-cosmos_T1_21", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Physical Laws Conditioning?", "ground_truth": ["Physical Laws Conditioning", "MECHANIS"], "concept_id": 21, "hop_depth": 0}
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| 24 |
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{"id": "nvidia-cosmos_T1_25", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Safety Filter?", "ground_truth": ["Safety Filter", "COMPONEN"], "concept_id": 25, "hop_depth": 0}
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| 25 |
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{"id": "nvidia-cosmos_T1_27", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is HuggingFace Release?", "ground_truth": ["HuggingFace Release", "DISTRIBU"], "concept_id": 27, "hop_depth": 0}
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| 26 |
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{"id": "nvidia-cosmos_T1_32", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Discrete Tokenizer?", "ground_truth": ["Discrete Tokenizer", "COMPONEN"], "concept_id": 32, "hop_depth": 0}
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| 27 |
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{"id": "nvidia-cosmos_T1_31", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Continuous Tokenizer?", "ground_truth": ["Continuous Tokenizer", "COMPONEN"], "concept_id": 31, "hop_depth": 0}
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| 28 |
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{"id": "nvidia-cosmos_T1_46", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is NVIDIA Cloud Functions (NVCF)?", "ground_truth": ["NVIDIA Cloud Functions (NVCF)", "PLATFORM"], "concept_id": 46, "hop_depth": 0}
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| 29 |
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{"id": "nvidia-cosmos_T1_40", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Conditioning Framework?", "ground_truth": ["Conditioning Framework", "MECHANIS"], "concept_id": 40, "hop_depth": 0}
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| 30 |
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{"id": "nvidia-cosmos_T1_36", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Edge Deployment?", "ground_truth": ["Edge Deployment", "PROCESS"], "concept_id": 36, "hop_depth": 0}
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| 31 |
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{"id": "nvidia-cosmos_T1_33", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is World State Representation?", "ground_truth": ["World State Representation", "CONCEPT"], "concept_id": 33, "hop_depth": 0}
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| 32 |
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{"id": "nvidia-cosmos_T1_12", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Diffusion WFM?", "ground_truth": ["Diffusion WFM", "ARCHITEC"], "concept_id": 12, "hop_depth": 0}
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| 33 |
+
{"id": "nvidia-cosmos_T1_26", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is NVIDIA Open Model License?", "ground_truth": ["NVIDIA Open Model License", "POLICY"], "concept_id": 26, "hop_depth": 0}
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| 34 |
+
{"id": "nvidia-cosmos_T1_42", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Physics Simulation Engine?", "ground_truth": ["Physics Simulation Engine", "TOOL"], "concept_id": 42, "hop_depth": 0}
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| 35 |
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{"id": "nvidia-cosmos_T1_5", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Cosmos-1.0-Reason?", "ground_truth": ["Cosmos-1.0-Reason", "MODEL"], "concept_id": 5, "hop_depth": 0}
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| 36 |
+
{"id": "nvidia-cosmos_T1_38", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is WFM Inference API?", "ground_truth": ["WFM Inference API", "API"], "concept_id": 38, "hop_depth": 0}
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| 37 |
+
{"id": "nvidia-cosmos_T1_4", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Cosmos Tokenizer?", "ground_truth": ["Cosmos Tokenizer", "TOOL"], "concept_id": 4, "hop_depth": 0}
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| 38 |
+
{"id": "nvidia-cosmos_T1_13", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Text-to-World Generation?", "ground_truth": ["Text-to-World Generation", "CAPABILI"], "concept_id": 13, "hop_depth": 0}
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| 39 |
+
{"id": "nvidia-cosmos_T1_34", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Multi-View Generation?", "ground_truth": ["Multi-View Generation", "CAPABILI"], "concept_id": 34, "hop_depth": 0}
|
| 40 |
+
{"id": "nvidia-cosmos_T1_30", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Video Diffusion Transformer (DiT)?", "ground_truth": ["Video Diffusion Transformer (DiT)", "ARCHITEC"], "concept_id": 30, "hop_depth": 0}
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| 41 |
+
{"id": "nvidia-cosmos_T1_10", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Video Tokenization?", "ground_truth": ["Video Tokenization", "PROCESS"], "concept_id": 10, "hop_depth": 0}
|
| 42 |
+
{"id": "nvidia-cosmos_T1_24", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Cosmos Dataset?", "ground_truth": ["Cosmos Dataset", "DATA"], "concept_id": 24, "hop_depth": 0}
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| 43 |
+
{"id": "nvidia-cosmos_T1_11", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Autoregressive WFM?", "ground_truth": ["Autoregressive WFM", "ARCHITEC"], "concept_id": 11, "hop_depth": 0}
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| 44 |
+
{"id": "nvidia-cosmos_T1_29", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Spatiotemporal Attention?", "ground_truth": ["Spatiotemporal Attention", "MECHANIS"], "concept_id": 29, "hop_depth": 0}
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| 45 |
+
{"id": "nvidia-cosmos_T1_22", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is Camera Model Conditioning?", "ground_truth": ["Camera Model Conditioning", "MECHANIS"], "concept_id": 22, "hop_depth": 0}
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| 46 |
+
{"id": "nvidia-cosmos_T1_19", "domain": "nvidia-cosmos", "type": "T1_entity", "query": "What is DRIVE Sim Integration?", "ground_truth": ["DRIVE Sim Integration", "INTEGRAT"], "concept_id": 19, "hop_depth": 0}
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| 47 |
+
{"id": "nvidia-cosmos_T2_39", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Generative World Simulation?", "ground_truth": ["Cosmos World Foundation Model"], "concept_id": 39, "hop_depth": 1}
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| 48 |
+
{"id": "nvidia-cosmos_T2_44", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Robot Manipulation?", "ground_truth": ["Robot Policy Training"], "concept_id": 44, "hop_depth": 1}
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| 49 |
+
{"id": "nvidia-cosmos_T2_8", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Synthetic Data Pipeline?", "ground_truth": ["3D Scene Generation", "Cosmos-1.0-Predict"], "concept_id": 8, "hop_depth": 1}
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| 50 |
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{"id": "nvidia-cosmos_T2_27", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for HuggingFace Release?", "ground_truth": ["NVIDIA Open Model License"], "concept_id": 27, "hop_depth": 1}
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| 51 |
+
{"id": "nvidia-cosmos_T2_6", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Cosmos-1.0-Nano?", "ground_truth": ["Edge Deployment", "Cosmos World Foundation Model"], "concept_id": 6, "hop_depth": 1}
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| 52 |
+
{"id": "nvidia-cosmos_T2_18", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Isaac Lab Integration?", "ground_truth": ["Robot Policy Training"], "concept_id": 18, "hop_depth": 1}
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| 53 |
+
{"id": "nvidia-cosmos_T2_10", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Video Tokenization?", "ground_truth": ["Cosmos Tokenizer"], "concept_id": 10, "hop_depth": 1}
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| 54 |
+
{"id": "nvidia-cosmos_T2_30", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Video Diffusion Transformer (DiT)?", "ground_truth": ["Spatiotemporal Attention"], "concept_id": 30, "hop_depth": 1}
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| 55 |
+
{"id": "nvidia-cosmos_T2_21", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Physical Laws Conditioning?", "ground_truth": ["Physics Simulation Engine"], "concept_id": 21, "hop_depth": 1}
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| 56 |
+
{"id": "nvidia-cosmos_T2_20", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for GR00T Integration?", "ground_truth": ["Robot Policy Training", "Isaac Lab Integration"], "concept_id": 20, "hop_depth": 1}
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| 57 |
+
{"id": "nvidia-cosmos_T2_12", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Diffusion WFM?", "ground_truth": ["Continuous Tokenizer", "Video Diffusion Transformer (DiT)"], "concept_id": 12, "hop_depth": 1}
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| 58 |
+
{"id": "nvidia-cosmos_T2_19", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for DRIVE Sim Integration?", "ground_truth": ["AV Scenario Simulation"], "concept_id": 19, "hop_depth": 1}
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| 59 |
+
{"id": "nvidia-cosmos_T2_7", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Physical AI?", "ground_truth": ["AV Scenario Simulation", "Robot Policy Training"], "concept_id": 7, "hop_depth": 1}
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| 60 |
+
{"id": "nvidia-cosmos_T2_23", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Action Conditioning?", "ground_truth": ["Conditioning Framework"], "concept_id": 23, "hop_depth": 1}
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| 61 |
+
{"id": "nvidia-cosmos_T2_3", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Cosmos-1.0-Transfer?", "ground_truth": ["Omniverse Integration", "Cosmos World Foundation Model"], "concept_id": 3, "hop_depth": 1}
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| 62 |
+
{"id": "nvidia-cosmos_T2_2", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Cosmos-1.0-Predict?", "ground_truth": ["Cosmos Tokenizer", "Action Conditioning", "Camera Model Conditioning", "Cosmos World Foundation Model"], "concept_id": 2, "hop_depth": 1}
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| 63 |
+
{"id": "nvidia-cosmos_T2_43", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Domain Randomization?", "ground_truth": ["Sim-to-Real Transfer"], "concept_id": 43, "hop_depth": 1}
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| 64 |
+
{"id": "nvidia-cosmos_T2_45", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for 3D Scene Generation?", "ground_truth": ["Omniverse Integration"], "concept_id": 45, "hop_depth": 1}
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| 65 |
+
{"id": "nvidia-cosmos_T2_22", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Camera Model Conditioning?", "ground_truth": ["Conditioning Framework"], "concept_id": 22, "hop_depth": 1}
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| 66 |
+
{"id": "nvidia-cosmos_T2_34", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Multi-View Generation?", "ground_truth": ["Camera Model Conditioning", "Cosmos-1.0-Predict"], "concept_id": 34, "hop_depth": 1}
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| 67 |
+
{"id": "nvidia-cosmos_T2_4", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Cosmos Tokenizer?", "ground_truth": ["Continuous Tokenizer", "Video Tokenization", "Discrete Tokenizer"], "concept_id": 4, "hop_depth": 1}
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| 68 |
+
{"id": "nvidia-cosmos_T2_24", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Cosmos Dataset?", "ground_truth": ["Teleoperation Data"], "concept_id": 24, "hop_depth": 1}
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| 69 |
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{"id": "nvidia-cosmos_T2_5", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Cosmos-1.0-Reason?", "ground_truth": ["Cosmos World Foundation Model"], "concept_id": 5, "hop_depth": 1}
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| 70 |
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{"id": "nvidia-cosmos_T2_17", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Omniverse Integration?", "ground_truth": ["3D Scene Generation"], "concept_id": 17, "hop_depth": 1}
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| 71 |
+
{"id": "nvidia-cosmos_T2_11", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Autoregressive WFM?", "ground_truth": ["Discrete Tokenizer"], "concept_id": 11, "hop_depth": 1}
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| 72 |
+
{"id": "nvidia-cosmos_T2_41", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Video Pretraining Corpus?", "ground_truth": ["Cosmos Dataset"], "concept_id": 41, "hop_depth": 1}
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| 73 |
+
{"id": "nvidia-cosmos_T2_40", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Conditioning Framework?", "ground_truth": ["Camera Model Conditioning", "Action Conditioning", "Text-to-World Generation"], "concept_id": 40, "hop_depth": 1}
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| 74 |
+
{"id": "nvidia-cosmos_T2_28", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Post-Training / Fine-Tuning?", "ground_truth": ["Cosmos Tokenizer", "NeMo Framework"], "concept_id": 28, "hop_depth": 1}
|
| 75 |
+
{"id": "nvidia-cosmos_T2_9", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Sim-to-Real Transfer?", "ground_truth": ["Omniverse Integration", "Cosmos-1.0-Transfer", "Domain Randomization"], "concept_id": 9, "hop_depth": 1}
|
| 76 |
+
{"id": "nvidia-cosmos_T2_33", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for World State Representation?", "ground_truth": ["Video Tokenization"], "concept_id": 33, "hop_depth": 1}
|
| 77 |
+
{"id": "nvidia-cosmos_T2_13", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Text-to-World Generation?", "ground_truth": ["Conditioning Framework", "Cosmos-1.0-Predict"], "concept_id": 13, "hop_depth": 1}
|
| 78 |
+
{"id": "nvidia-cosmos_T2_42", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Physics Simulation Engine?", "ground_truth": ["Omniverse Integration"], "concept_id": 42, "hop_depth": 1}
|
| 79 |
+
{"id": "nvidia-cosmos_T2_1", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Cosmos World Foundation Model?", "ground_truth": ["Diffusion WFM", "Video Pretraining Corpus", "Autoregressive WFM", "Cosmos Dataset", "Spatiotemporal Attention", "Physical Laws Conditioning"], "concept_id": 1, "hop_depth": 1}
|
| 80 |
+
{"id": "nvidia-cosmos_T2_14", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Video-to-World Prediction?", "ground_truth": ["Video Tokenization", "Cosmos-1.0-Predict"], "concept_id": 14, "hop_depth": 1}
|
| 81 |
+
{"id": "nvidia-cosmos_T2_16", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for AV Scenario Simulation?", "ground_truth": ["Camera Model Conditioning", "Physical AI", "Cosmos-1.0-Predict", "Text-to-World Generation"], "concept_id": 16, "hop_depth": 1}
|
| 82 |
+
{"id": "nvidia-cosmos_T2_15", "domain": "nvidia-cosmos", "type": "T2_dependency", "query": "What are the prerequisites for Robot Policy Training?", "ground_truth": ["Action Conditioning", "Physical AI", "Synthetic Data Pipeline", "Domain Randomization"], "concept_id": 15, "hop_depth": 1}
|
| 83 |
+
{"id": "nvidia-cosmos_T3_32_6", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Discrete Tokenizer to Cosmos-1.0-Nano?", "ground_truth": ["Cosmos-1.0-Nano", "Cosmos World Foundation Model", "Autoregressive WFM", "Discrete Tokenizer"], "concept_id": 6, "hop_depth": 3, "path_ids": [6, 1, 11, 32]}
|
| 84 |
+
{"id": "nvidia-cosmos_T3_31_34", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Continuous Tokenizer to Multi-View Generation?", "ground_truth": ["Multi-View Generation", "Cosmos-1.0-Predict", "Cosmos Tokenizer", "Continuous Tokenizer"], "concept_id": 34, "hop_depth": 3, "path_ids": [34, 2, 4, 31]}
|
| 85 |
+
{"id": "nvidia-cosmos_T3_35_19", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Teleoperation Data to DRIVE Sim Integration?", "ground_truth": ["DRIVE Sim Integration", "AV Scenario Simulation", "Cosmos-1.0-Predict", "Cosmos World Foundation Model", "Cosmos Dataset", "Teleoperation Data"], "concept_id": 19, "hop_depth": 5, "path_ids": [19, 16, 2, 1, 24, 35]}
|
| 86 |
+
{"id": "nvidia-cosmos_T3_32_14", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Discrete Tokenizer to Video-to-World Prediction?", "ground_truth": ["Video-to-World Prediction", "Video Tokenization", "Cosmos Tokenizer", "Discrete Tokenizer"], "concept_id": 14, "hop_depth": 3, "path_ids": [14, 10, 4, 32]}
|
| 87 |
+
{"id": "nvidia-cosmos_T3_31_39", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Continuous Tokenizer to Generative World Simulation?", "ground_truth": ["Generative World Simulation", "Cosmos World Foundation Model", "Diffusion WFM", "Continuous Tokenizer"], "concept_id": 39, "hop_depth": 3, "path_ids": [39, 1, 12, 31]}
|
| 88 |
+
{"id": "nvidia-cosmos_T3_32_39", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Discrete Tokenizer to Generative World Simulation?", "ground_truth": ["Generative World Simulation", "Cosmos World Foundation Model", "Autoregressive WFM", "Discrete Tokenizer"], "concept_id": 39, "hop_depth": 3, "path_ids": [39, 1, 11, 32]}
|
| 89 |
+
{"id": "nvidia-cosmos_T3_35_19", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Teleoperation Data to DRIVE Sim Integration?", "ground_truth": ["DRIVE Sim Integration", "AV Scenario Simulation", "Cosmos-1.0-Predict", "Cosmos World Foundation Model", "Cosmos Dataset", "Teleoperation Data"], "concept_id": 19, "hop_depth": 5, "path_ids": [19, 16, 2, 1, 24, 35]}
|
| 90 |
+
{"id": "nvidia-cosmos_T3_29_44", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Spatiotemporal Attention to Robot Manipulation?", "ground_truth": ["Robot Manipulation", "Robot Policy Training", "Synthetic Data Pipeline", "Cosmos-1.0-Predict", "Cosmos World Foundation Model", "Spatiotemporal Attention"], "concept_id": 44, "hop_depth": 5, "path_ids": [44, 15, 8, 2, 1, 29]}
|
| 91 |
+
{"id": "nvidia-cosmos_T3_26_27", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from NVIDIA Open Model License to HuggingFace Release?", "ground_truth": ["HuggingFace Release", "NVIDIA Open Model License"], "concept_id": 27, "hop_depth": 1, "path_ids": [27, 26]}
|
| 92 |
+
{"id": "nvidia-cosmos_T3_32_33", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Discrete Tokenizer to World State Representation?", "ground_truth": ["World State Representation", "Video Tokenization", "Cosmos Tokenizer", "Discrete Tokenizer"], "concept_id": 33, "hop_depth": 3, "path_ids": [33, 10, 4, 32]}
|
| 93 |
+
{"id": "nvidia-cosmos_T3_32_44", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Discrete Tokenizer to Robot Manipulation?", "ground_truth": ["Robot Manipulation", "Robot Policy Training", "Synthetic Data Pipeline", "Cosmos-1.0-Predict", "Cosmos Tokenizer", "Discrete Tokenizer"], "concept_id": 44, "hop_depth": 5, "path_ids": [44, 15, 8, 2, 4, 32]}
|
| 94 |
+
{"id": "nvidia-cosmos_T3_35_6", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Teleoperation Data to Cosmos-1.0-Nano?", "ground_truth": ["Cosmos-1.0-Nano", "Cosmos World Foundation Model", "Cosmos Dataset", "Teleoperation Data"], "concept_id": 6, "hop_depth": 3, "path_ids": [6, 1, 24, 35]}
|
| 95 |
+
{"id": "nvidia-cosmos_T3_32_33", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Discrete Tokenizer to World State Representation?", "ground_truth": ["World State Representation", "Video Tokenization", "Cosmos Tokenizer", "Discrete Tokenizer"], "concept_id": 33, "hop_depth": 3, "path_ids": [33, 10, 4, 32]}
|
| 96 |
+
{"id": "nvidia-cosmos_T3_31_14", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Continuous Tokenizer to Video-to-World Prediction?", "ground_truth": ["Video-to-World Prediction", "Video Tokenization", "Cosmos Tokenizer", "Continuous Tokenizer"], "concept_id": 14, "hop_depth": 3, "path_ids": [14, 10, 4, 31]}
|
| 97 |
+
{"id": "nvidia-cosmos_T3_32_19", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Discrete Tokenizer to DRIVE Sim Integration?", "ground_truth": ["DRIVE Sim Integration", "AV Scenario Simulation", "Cosmos-1.0-Predict", "Cosmos Tokenizer", "Discrete Tokenizer"], "concept_id": 19, "hop_depth": 4, "path_ids": [19, 16, 2, 4, 32]}
|
| 98 |
+
{"id": "nvidia-cosmos_T3_29_14", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Spatiotemporal Attention to Video-to-World Prediction?", "ground_truth": ["Video-to-World Prediction", "Cosmos-1.0-Predict", "Cosmos World Foundation Model", "Spatiotemporal Attention"], "concept_id": 14, "hop_depth": 3, "path_ids": [14, 2, 1, 29]}
|
| 99 |
+
{"id": "nvidia-cosmos_T3_29_20", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Spatiotemporal Attention to GR00T Integration?", "ground_truth": ["GR00T Integration", "Robot Policy Training", "Synthetic Data Pipeline", "Cosmos-1.0-Predict", "Cosmos World Foundation Model", "Spatiotemporal Attention"], "concept_id": 20, "hop_depth": 5, "path_ids": [20, 15, 8, 2, 1, 29]}
|
| 100 |
+
{"id": "nvidia-cosmos_T3_31_33", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Continuous Tokenizer to World State Representation?", "ground_truth": ["World State Representation", "Video Tokenization", "Cosmos Tokenizer", "Continuous Tokenizer"], "concept_id": 33, "hop_depth": 3, "path_ids": [33, 10, 4, 31]}
|
| 101 |
+
{"id": "nvidia-cosmos_T3_31_39", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Continuous Tokenizer to Generative World Simulation?", "ground_truth": ["Generative World Simulation", "Cosmos World Foundation Model", "Diffusion WFM", "Continuous Tokenizer"], "concept_id": 39, "hop_depth": 3, "path_ids": [39, 1, 12, 31]}
|
| 102 |
+
{"id": "nvidia-cosmos_T3_31_6", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Continuous Tokenizer to Cosmos-1.0-Nano?", "ground_truth": ["Cosmos-1.0-Nano", "Cosmos World Foundation Model", "Diffusion WFM", "Continuous Tokenizer"], "concept_id": 6, "hop_depth": 3, "path_ids": [6, 1, 12, 31]}
|
| 103 |
+
{"id": "nvidia-cosmos_T3_35_5", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Teleoperation Data to Cosmos-1.0-Reason?", "ground_truth": ["Cosmos-1.0-Reason", "Cosmos World Foundation Model", "Cosmos Dataset", "Teleoperation Data"], "concept_id": 5, "hop_depth": 3, "path_ids": [5, 1, 24, 35]}
|
| 104 |
+
{"id": "nvidia-cosmos_T3_31_34", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Continuous Tokenizer to Multi-View Generation?", "ground_truth": ["Multi-View Generation", "Cosmos-1.0-Predict", "Cosmos Tokenizer", "Continuous Tokenizer"], "concept_id": 34, "hop_depth": 3, "path_ids": [34, 2, 4, 31]}
|
| 105 |
+
{"id": "nvidia-cosmos_T3_31_5", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Continuous Tokenizer to Cosmos-1.0-Reason?", "ground_truth": ["Cosmos-1.0-Reason", "Cosmos World Foundation Model", "Diffusion WFM", "Continuous Tokenizer"], "concept_id": 5, "hop_depth": 3, "path_ids": [5, 1, 12, 31]}
|
| 106 |
+
{"id": "nvidia-cosmos_T3_35_6", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Teleoperation Data to Cosmos-1.0-Nano?", "ground_truth": ["Cosmos-1.0-Nano", "Cosmos World Foundation Model", "Cosmos Dataset", "Teleoperation Data"], "concept_id": 6, "hop_depth": 3, "path_ids": [6, 1, 24, 35]}
|
| 107 |
+
{"id": "nvidia-cosmos_T3_31_19", "domain": "nvidia-cosmos", "type": "T3_path", "query": "What is the prerequisite chain from Continuous Tokenizer to DRIVE Sim Integration?", "ground_truth": ["DRIVE Sim Integration", "AV Scenario Simulation", "Cosmos-1.0-Predict", "Cosmos Tokenizer", "Continuous Tokenizer"], "concept_id": 19, "hop_depth": 4, "path_ids": [19, 16, 2, 4, 31]}
|
| 108 |
+
{"id": "nvidia-cosmos_T4_PLATFORM", "domain": "nvidia-cosmos", "type": "T4_aggregate", "query": "List all PLATFORM concepts in this knowledge graph", "ground_truth": ["Cosmos World Foundation Model", "NVIDIA Cloud Functions (NVCF)"], "taxonomy_id": "PLATFORM", "hop_depth": 0}
|
| 109 |
+
{"id": "nvidia-cosmos_T4_MODEL", "domain": "nvidia-cosmos", "type": "T4_aggregate", "query": "List all MODEL concepts in this knowledge graph", "ground_truth": ["Cosmos-1.0-Predict", "Cosmos-1.0-Transfer", "Cosmos-1.0-Reason", "Cosmos-1.0-Nano"], "taxonomy_id": "MODEL", "hop_depth": 0}
|
| 110 |
+
{"id": "nvidia-cosmos_T4_TOOL", "domain": "nvidia-cosmos", "type": "T4_aggregate", "query": "List all TOOL concepts in this knowledge graph", "ground_truth": ["Cosmos Tokenizer", "NeMo Framework", "Physics Simulation Engine"], "taxonomy_id": "TOOL", "hop_depth": 0}
|
| 111 |
+
{"id": "nvidia-cosmos_T4_CONCEPT", "domain": "nvidia-cosmos", "type": "T4_aggregate", "query": "List all CONCEPT concepts in this knowledge graph", "ground_truth": ["Physical AI", "Sim-to-Real Transfer", "World State Representation", "Generative World Simulation"], "taxonomy_id": "CONCEPT", "hop_depth": 0}
|
| 112 |
+
{"id": "nvidia-cosmos_T4_PIPELINE", "domain": "nvidia-cosmos", "type": "T4_aggregate", "query": "List all PIPELINE concepts in this knowledge graph", "ground_truth": ["Synthetic Data Pipeline"], "taxonomy_id": "PIPELINE", "hop_depth": 0}
|
| 113 |
+
{"id": "nvidia-cosmos_T4_PROCESS", "domain": "nvidia-cosmos", "type": "T4_aggregate", "query": "List all PROCESS concepts in this knowledge graph", "ground_truth": ["Video Tokenization", "Robot Policy Training", "AV Scenario Simulation", "Post-Training / Fine-Tuning", "Edge Deployment"], "taxonomy_id": "PROCESS", "hop_depth": 0}
|
| 114 |
+
{"id": "nvidia-cosmos_T4_ARCHITEC", "domain": "nvidia-cosmos", "type": "T4_aggregate", "query": "List all ARCHITEC concepts in this knowledge graph", "ground_truth": ["Autoregressive WFM", "Diffusion WFM", "Video Diffusion Transformer (DiT)"], "taxonomy_id": "ARCHITEC", "hop_depth": 0}
|
| 115 |
+
{"id": "nvidia-cosmos_T4_CAPABILI", "domain": "nvidia-cosmos", "type": "T4_aggregate", "query": "List all CAPABILI concepts in this knowledge graph", "ground_truth": ["Text-to-World Generation", "Video-to-World Prediction", "Multi-View Generation", "Robot Manipulation", "3D Scene Generation"], "taxonomy_id": "CAPABILI", "hop_depth": 0}
|
| 116 |
+
{"id": "nvidia-cosmos_T4_INTEGRAT", "domain": "nvidia-cosmos", "type": "T4_aggregate", "query": "List all INTEGRAT concepts in this knowledge graph", "ground_truth": ["Omniverse Integration", "Isaac Lab Integration", "DRIVE Sim Integration", "GR00T Integration"], "taxonomy_id": "INTEGRAT", "hop_depth": 0}
|
| 117 |
+
{"id": "nvidia-cosmos_T4_MECHANIS", "domain": "nvidia-cosmos", "type": "T4_aggregate", "query": "List all MECHANIS concepts in this knowledge graph", "ground_truth": ["Physical Laws Conditioning", "Camera Model Conditioning", "Action Conditioning", "Spatiotemporal Attention", "Conditioning Framework"], "taxonomy_id": "MECHANIS", "hop_depth": 0}
|
| 118 |
+
{"id": "nvidia-cosmos_T4_DATA", "domain": "nvidia-cosmos", "type": "T4_aggregate", "query": "List all DATA concepts in this knowledge graph", "ground_truth": ["Cosmos Dataset", "Teleoperation Data", "Video Pretraining Corpus"], "taxonomy_id": "DATA", "hop_depth": 0}
|
| 119 |
+
{"id": "nvidia-cosmos_T4_COMPONEN", "domain": "nvidia-cosmos", "type": "T4_aggregate", "query": "List all COMPONEN concepts in this knowledge graph", "ground_truth": ["Safety Filter", "Continuous Tokenizer", "Discrete Tokenizer"], "taxonomy_id": "COMPONEN", "hop_depth": 0}
|
| 120 |
+
{"id": "nvidia-cosmos_T4_POLICY", "domain": "nvidia-cosmos", "type": "T4_aggregate", "query": "List all POLICY concepts in this knowledge graph", "ground_truth": ["NVIDIA Open Model License"], "taxonomy_id": "POLICY", "hop_depth": 0}
|
| 121 |
+
{"id": "nvidia-cosmos_T4_DISTRIBU", "domain": "nvidia-cosmos", "type": "T4_aggregate", "query": "List all DISTRIBU concepts in this knowledge graph", "ground_truth": ["HuggingFace Release"], "taxonomy_id": "DISTRIBU", "hop_depth": 0}
|
| 122 |
+
{"id": "nvidia-cosmos_T4_API", "domain": "nvidia-cosmos", "type": "T4_aggregate", "query": "List all API concepts in this knowledge graph", "ground_truth": ["WFM Inference API"], "taxonomy_id": "API", "hop_depth": 0}
|
| 123 |
+
{"id": "nvidia-cosmos_T4_TECHNIQU", "domain": "nvidia-cosmos", "type": "T4_aggregate", "query": "List all TECHNIQU concepts in this knowledge graph", "ground_truth": ["Domain Randomization"], "taxonomy_id": "TECHNIQU", "hop_depth": 0}
|
| 124 |
+
{"id": "nvidia-cosmos_T5_39_1", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Generative World Simulation relate to Cosmos World Foundation Model?", "ground_truth": ["Generative World Simulation", "Cosmos World Foundation Model"], "concept_id_a": 39, "concept_id_b": 1, "hop_depth": 1}
|
| 125 |
+
{"id": "nvidia-cosmos_T5_6_1", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Cosmos-1.0-Nano relate to Cosmos World Foundation Model?", "ground_truth": ["Cosmos-1.0-Nano", "Cosmos World Foundation Model"], "concept_id_a": 6, "concept_id_b": 1, "hop_depth": 1}
|
| 126 |
+
{"id": "nvidia-cosmos_T5_33_10", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does World State Representation relate to Video Tokenization?", "ground_truth": ["World State Representation", "Video Tokenization"], "concept_id_a": 33, "concept_id_b": 10, "hop_depth": 1}
|
| 127 |
+
{"id": "nvidia-cosmos_T5_3_1", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Cosmos-1.0-Transfer relate to Cosmos World Foundation Model?", "ground_truth": ["Cosmos-1.0-Transfer", "Cosmos World Foundation Model"], "concept_id_a": 3, "concept_id_b": 1, "hop_depth": 1}
|
| 128 |
+
{"id": "nvidia-cosmos_T5_44_15", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Robot Manipulation relate to Robot Policy Training?", "ground_truth": ["Robot Manipulation", "Robot Policy Training"], "concept_id_a": 44, "concept_id_b": 15, "hop_depth": 1}
|
| 129 |
+
{"id": "nvidia-cosmos_T5_13_40", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Text-to-World Generation relate to Conditioning Framework?", "ground_truth": ["Text-to-World Generation", "Conditioning Framework"], "concept_id_a": 13, "concept_id_b": 40, "hop_depth": 1}
|
| 130 |
+
{"id": "nvidia-cosmos_T5_5_1", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Cosmos-1.0-Reason relate to Cosmos World Foundation Model?", "ground_truth": ["Cosmos-1.0-Reason", "Cosmos World Foundation Model"], "concept_id_a": 5, "concept_id_b": 1, "hop_depth": 1}
|
| 131 |
+
{"id": "nvidia-cosmos_T5_34_22", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Multi-View Generation relate to Camera Model Conditioning?", "ground_truth": ["Multi-View Generation", "Camera Model Conditioning"], "concept_id_a": 34, "concept_id_b": 22, "hop_depth": 1}
|
| 132 |
+
{"id": "nvidia-cosmos_T5_1_29", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Cosmos World Foundation Model relate to Spatiotemporal Attention?", "ground_truth": ["Cosmos World Foundation Model", "Spatiotemporal Attention"], "concept_id_a": 1, "concept_id_b": 29, "hop_depth": 1}
|
| 133 |
+
{"id": "nvidia-cosmos_T5_12_30", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Diffusion WFM relate to Video Diffusion Transformer (DiT)?", "ground_truth": ["Diffusion WFM", "Video Diffusion Transformer (DiT)"], "concept_id_a": 12, "concept_id_b": 30, "hop_depth": 1}
|
| 134 |
+
{"id": "nvidia-cosmos_T5_28_4", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Post-Training / Fine-Tuning relate to Cosmos Tokenizer?", "ground_truth": ["Post-Training / Fine-Tuning", "Cosmos Tokenizer"], "concept_id_a": 28, "concept_id_b": 4, "hop_depth": 1}
|
| 135 |
+
{"id": "nvidia-cosmos_T5_43_9", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Domain Randomization relate to Sim-to-Real Transfer?", "ground_truth": ["Domain Randomization", "Sim-to-Real Transfer"], "concept_id_a": 43, "concept_id_b": 9, "hop_depth": 1}
|
| 136 |
+
{"id": "nvidia-cosmos_T5_15_8", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Robot Policy Training relate to Synthetic Data Pipeline?", "ground_truth": ["Robot Policy Training", "Synthetic Data Pipeline"], "concept_id_a": 15, "concept_id_b": 8, "hop_depth": 1}
|
| 137 |
+
{"id": "nvidia-cosmos_T5_2_4", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Cosmos-1.0-Predict relate to Cosmos Tokenizer?", "ground_truth": ["Cosmos-1.0-Predict", "Cosmos Tokenizer"], "concept_id_a": 2, "concept_id_b": 4, "hop_depth": 1}
|
| 138 |
+
{"id": "nvidia-cosmos_T5_1_24", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Cosmos World Foundation Model relate to Cosmos Dataset?", "ground_truth": ["Cosmos World Foundation Model", "Cosmos Dataset"], "concept_id_a": 1, "concept_id_b": 24, "hop_depth": 1}
|
| 139 |
+
{"id": "nvidia-cosmos_T5_17_45", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Omniverse Integration relate to 3D Scene Generation?", "ground_truth": ["Omniverse Integration", "3D Scene Generation"], "concept_id_a": 17, "concept_id_b": 45, "hop_depth": 1}
|
| 140 |
+
{"id": "nvidia-cosmos_T5_15_7", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Robot Policy Training relate to Physical AI?", "ground_truth": ["Robot Policy Training", "Physical AI"], "concept_id_a": 15, "concept_id_b": 7, "hop_depth": 1}
|
| 141 |
+
{"id": "nvidia-cosmos_T5_1_12", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Cosmos World Foundation Model relate to Diffusion WFM?", "ground_truth": ["Cosmos World Foundation Model", "Diffusion WFM"], "concept_id_a": 1, "concept_id_b": 12, "hop_depth": 1}
|
| 142 |
+
{"id": "nvidia-cosmos_T5_1_21", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Cosmos World Foundation Model relate to Physical Laws Conditioning?", "ground_truth": ["Cosmos World Foundation Model", "Physical Laws Conditioning"], "concept_id_a": 1, "concept_id_b": 21, "hop_depth": 1}
|
| 143 |
+
{"id": "nvidia-cosmos_T5_40_23", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Conditioning Framework relate to Action Conditioning?", "ground_truth": ["Conditioning Framework", "Action Conditioning"], "concept_id_a": 40, "concept_id_b": 23, "hop_depth": 1}
|
| 144 |
+
{"id": "nvidia-cosmos_T5_3_17", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Cosmos-1.0-Transfer relate to Omniverse Integration?", "ground_truth": ["Cosmos-1.0-Transfer", "Omniverse Integration"], "concept_id_a": 3, "concept_id_b": 17, "hop_depth": 1}
|
| 145 |
+
{"id": "nvidia-cosmos_T5_11_32", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Autoregressive WFM relate to Discrete Tokenizer?", "ground_truth": ["Autoregressive WFM", "Discrete Tokenizer"], "concept_id_a": 11, "concept_id_b": 32, "hop_depth": 1}
|
| 146 |
+
{"id": "nvidia-cosmos_T5_14_10", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Video-to-World Prediction relate to Video Tokenization?", "ground_truth": ["Video-to-World Prediction", "Video Tokenization"], "concept_id_a": 14, "concept_id_b": 10, "hop_depth": 1}
|
| 147 |
+
{"id": "nvidia-cosmos_T5_13_2", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Text-to-World Generation relate to Cosmos-1.0-Predict?", "ground_truth": ["Text-to-World Generation", "Cosmos-1.0-Predict"], "concept_id_a": 13, "concept_id_b": 2, "hop_depth": 1}
|
| 148 |
+
{"id": "nvidia-cosmos_T5_4_10", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Cosmos Tokenizer relate to Video Tokenization?", "ground_truth": ["Cosmos Tokenizer", "Video Tokenization"], "concept_id_a": 4, "concept_id_b": 10, "hop_depth": 1}
|
| 149 |
+
{"id": "nvidia-cosmos_T5_10_4", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Video Tokenization relate to Cosmos Tokenizer?", "ground_truth": ["Video Tokenization", "Cosmos Tokenizer"], "concept_id_a": 10, "concept_id_b": 4, "hop_depth": 1}
|
| 150 |
+
{"id": "nvidia-cosmos_T5_40_22", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Conditioning Framework relate to Camera Model Conditioning?", "ground_truth": ["Conditioning Framework", "Camera Model Conditioning"], "concept_id_a": 40, "concept_id_b": 22, "hop_depth": 1}
|
| 151 |
+
{"id": "nvidia-cosmos_T5_20_18", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does GR00T Integration relate to Isaac Lab Integration?", "ground_truth": ["GR00T Integration", "Isaac Lab Integration", "Robot Policy Training"], "concept_id_a": 20, "concept_id_b": 18, "hop_depth": 1}
|
| 152 |
+
{"id": "nvidia-cosmos_T5_9_43", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Sim-to-Real Transfer relate to Domain Randomization?", "ground_truth": ["Sim-to-Real Transfer", "Domain Randomization"], "concept_id_a": 9, "concept_id_b": 43, "hop_depth": 1}
|
| 153 |
+
{"id": "nvidia-cosmos_T5_23_40", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Action Conditioning relate to Conditioning Framework?", "ground_truth": ["Action Conditioning", "Conditioning Framework"], "concept_id_a": 23, "concept_id_b": 40, "hop_depth": 1}
|
| 154 |
+
{"id": "nvidia-cosmos_T5_16_22", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does AV Scenario Simulation relate to Camera Model Conditioning?", "ground_truth": ["AV Scenario Simulation", "Camera Model Conditioning"], "concept_id_a": 16, "concept_id_b": 22, "hop_depth": 1}
|
| 155 |
+
{"id": "nvidia-cosmos_T5_6_36", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Cosmos-1.0-Nano relate to Edge Deployment?", "ground_truth": ["Cosmos-1.0-Nano", "Edge Deployment"], "concept_id_a": 6, "concept_id_b": 36, "hop_depth": 1}
|
| 156 |
+
{"id": "nvidia-cosmos_T5_40_13", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Conditioning Framework relate to Text-to-World Generation?", "ground_truth": ["Conditioning Framework", "Text-to-World Generation"], "concept_id_a": 40, "concept_id_b": 13, "hop_depth": 1}
|
| 157 |
+
{"id": "nvidia-cosmos_T5_7_16", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Physical AI relate to AV Scenario Simulation?", "ground_truth": ["Physical AI", "AV Scenario Simulation"], "concept_id_a": 7, "concept_id_b": 16, "hop_depth": 1}
|
| 158 |
+
{"id": "nvidia-cosmos_T5_12_31", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Diffusion WFM relate to Continuous Tokenizer?", "ground_truth": ["Diffusion WFM", "Continuous Tokenizer"], "concept_id_a": 12, "concept_id_b": 31, "hop_depth": 1}
|
| 159 |
+
{"id": "nvidia-cosmos_T5_9_17", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Sim-to-Real Transfer relate to Omniverse Integration?", "ground_truth": ["Sim-to-Real Transfer", "Omniverse Integration"], "concept_id_a": 9, "concept_id_b": 17, "hop_depth": 1}
|
| 160 |
+
{"id": "nvidia-cosmos_T5_9_3", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does Sim-to-Real Transfer relate to Cosmos-1.0-Transfer?", "ground_truth": ["Sim-to-Real Transfer", "Cosmos-1.0-Transfer", "Omniverse Integration"], "concept_id_a": 9, "concept_id_b": 3, "hop_depth": 1}
|
| 161 |
+
{"id": "nvidia-cosmos_T5_16_13", "domain": "nvidia-cosmos", "type": "T5_cross_concept", "query": "How does AV Scenario Simulation relate to Text-to-World Generation?", "ground_truth": ["AV Scenario Simulation", "Text-to-World Generation", "Cosmos-1.0-Predict"], "concept_id_a": 16, "concept_id_b": 13, "hop_depth": 1}
|