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cs.CL2024★ 2 cited
Evaluating Language Model Context Windows: A "Working Memory" Test and Inference-time Correction
Amanda Dsouza, Christopher Glaze, Changho Shin +1
Large language models are prominently used in real-world applications, often tasked with reasoning over large volumes of documents. An exciting development in this space is models…
cs.CL2023★ 4 cited
Skill-it! A Data-Driven Skills Framework for Understanding and Training Language Models
Mayee F. Chen, Nicholas Roberts, Kush Bhatia +4
The quality of training data impacts the performance of pre-trained large language models (LMs). Given a fixed budget of tokens, we study how to best select data that leads to good…