Benhao Huang is an M.S. student in Machine Learning at Carnegie Mellon University and a researcher in the Locus Lab. His work focuses on loop-model architectures, scalable reasoning, LLM pre-training, and efficient model training. Previously, he worked on world models, dataset-curation agents, and AI interpretability.
Benhao Huang is an M.S. student in Machine Learning at Carnegie Mellon University and a researcher in the Locus Lab. His work focuses on loop-model architectures, scalable reasoning, LLM pre-training, and efficient model training. Previously, he worked on world models, dataset-curation agents, and AI interpretability.