Papers by Ryan Daniels

1 papers
Pico: A Modular Framework for Hypothesis-Driven Small Language Model Research (2025.emnlp-demos)

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Challenge: Recent advances in large language models (LLMs) have enabled strong performance across diverse tasks, but small enough to train on modest budgets.
Approach: They propose a lightweight, modular framework that enables systematic, hypothesis-driven research for small and medium-scale language model development.
Outcome: The proposed framework enables systematic, hypothesis-driven research for small and medium-scale language model development.

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