“Large Language Models (LLMs) have yielded fast and dramatic progress in NLP, and now offer strong few- and zero-shot capabilities on new tasks, reducing the need for annotation. This is especially exciting for the medical domain, in which supervision is often scant and expensive. At the same time, model predictions are rarely so accurate that they can be trusted blindly. … We propose CHiLL (Crafting High-Level Latents), which uses LLMs to permit natural language specification of high-level features for linear models via zero-shot feature extraction using expert-composed queries.”

Find the paper and the full list of authors in ArXiv.