synthetic dataset
A synthetic dataset is artificially generated data created to simulate real-world scenarios. In AI, synthetic datasets are often used for training models, especially when real data is scarce or difficult to obtain, allowing researchers to create diverse and labeled examples for testing purposes.
- Causal Climate Emulation with Bayesian Filtering
- ChartMuseum: Testing Visual Reasoning Capabilities of Large Vision-Language Models
- Contextual Integrity in LLMs via Reasoning and Reinforcement Learning
- DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos
- Dataset Distillation of 3D Point Clouds via Distribution Matching
- Detecting High-Stakes Interactions with Activation Probes
- Mellow: a small audio language model for reasoning
- MesaTask: Towards Task-Driven Tabletop Scene Generation via 3D Spatial Reasoning
- MoodAngels: A Retrieval-augmented Multi-agent Framework for Psychiatry Diagnosis
- ORBIT - Open Recommendation Benchmark for Reproducible Research with Hidden Tests
- SpatialLM: Training Large Language Models for Structured Indoor Modeling
- Towards Predicting Any Human Trajectory In Context
- VideoCAD: A Dataset and Model for Learning Long‑Horizon 3D CAD UI Interactions from Video