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cs.CL2025★ 1 cited
Rapid Word Learning Through Meta In-Context Learning
Wentao Wang, Guangyuan Jiang, Tal Linzen +1
Humans can quickly learn a new word from a few illustrative examples, and then systematically and flexibly use it in novel contexts. Yet the abilities of current language models fo…
cs.CL2024★ 1 cited
CoLLEGe: Concept Embedding Generation for Large Language Models
Ryan Teehan, Brenden Lake, Mengye Ren
Current language models are unable to quickly learn new concepts on the fly, often requiring a more involved finetuning process to learn robustly. Prompting in-context is not robus…