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C. Daniel Guetta

2 accepted papers

2025

Architectural and Inferential Inductive Biases for Exchangeable Sequence Modeling

NeurIPS 2025poster

Autoregressive models have emerged as a powerful framework for modeling exchangeable sequences---i.i.d. observations when conditioned on some latent factor---enabling direct modeling of uncertainty from missing data (rather than a latent). Motivated by the critical role posterior inference plays as…

Cited by 0SourcecodeScholar
2025

Data Mixture Optimization: A Multi-fidelity Multi-scale Bayesian Framework

NeurIPS 2025poster

Careful curation of data sources can significantly improve the performance of LLM pre-training, but predominant approaches rely heavily on intuition or costly trial-and-error, making them difficult to generalize across different data domains and downstream tasks. Although scaling laws can provide a…

Cited by 0SourcecodeScholar