real-world dataset
Datasets that are collected from real-world scenarios as opposed to synthetic or simulated datasets, often containing noise, bias, and complexity that model designers must consider. They are essential for training robust and applicable AI systems.
- Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond)
- Differentiable Constraint-Based Causal Discovery
- Discovering Opinion Intervals from Conflicts in Signed Graphs
- Discovering Opinion Intervals from Conflicts in Signed Graphs
- Toward Artificial Palpation: Representation Learning of Touch on Soft Bodies