An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models

Supervised finetuning (SFT) on instruction datasets has played a crucial role in achieving the remarkable zero-shot generalization capabilities observed in modern large language models (LLMs). However, the annotation efforts required to produce high quality responses for instructions are becoming pr...

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Hauptverfasser:	Bhatt, Gantavya, Chen, Yifang, Das, Arnav M, Zhang, Jifan, Truong, Sang T, Mussmann, Stephen, Zhu, Yinglun, Bilmes, Jeffrey, Du, Simon S, Jamieson, Kevin, Ash, Jordan T, Nowak, Robert D
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Computation and Language Computer Science - Learning
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