2.7k citations · 2.9k across the 8 of their papers we have counts for
3 papers · 1 filter
Correlating and Predicting Human Evaluations of Language Models from Natural Language Processing Benchmarks
Rylan Schaeffer, Punit Singh Koura, Binh Tang +11
The explosion of high-performing conversational language models (LMs) has spurred a shift from classic natural language processing (NLP) benchmarks to expensive, time-consuming and…
BTS: Harmonizing Specialized Experts into a Generalist LLM
Qizhen Zhang, Prajjwal Bhargava, Chloe Bi +9
We present Branch-Train-Stitch (BTS), an efficient and flexible training algorithm for combining independently trained large language model (LLM) experts into a single, capable gen…
Optimizing Pretraining Data Mixtures with LLM-Estimated Utility
William Held, Bhargavi Paranjape, Punit Singh Koura +3
Large Language Models improve with increasing amounts of high-quality training data. However, leveraging larger datasets requires balancing quality, quantity, and diversity across…