1 citations · 1 across the 10 of their papers we have counts for
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Smoothie: Label Free Language Model Routing
Neel Guha, Mayee F. Chen, Trevor Chow +2
Large language models (LLMs) are increasingly used in applications where LLM inputs may span many different tasks. Recent work has found that the choice of LLM is consequential, an…
Aioli: A Unified Optimization Framework for Language Model Data Mixing
Mayee F. Chen, Michael Y. Hu, Nicholas Lourie +2
Language model performance depends on identifying the optimal mixture of data groups to train on (e.g., law, code, math). Prior work has proposed a diverse set of methods to effici…
Automated Rewards via LLM-Generated Progress Functions
Vishnu Sarukkai, Brennan Shacklett, Zander Majercik +3
Large Language Models (LLMs) have the potential to automate reward engineering by leveraging their broad domain knowledge across various tasks. However, they often need many iterat…
Cookbook: A framework for improving LLM generative abilities via programmatic data generating templates
Avanika Narayan, Mayee F. Chen, Kush Bhatia +1
Fine-tuning large language models (LLMs) on instruction datasets is a common way to improve their generative capabilities. However, instruction datasets can be expensive and time-c…