ought/raft
Large pre-trained language models have shown promise for few-shot learning, completing text-based tasks given only a few task-specific examples. Will models soon solve classification tasks that have so far been reserved for human research assistants? [RAFT](https://raft.elicit.org) is a few-shot classification benchmark that tests language models: - across multiple domains (lit review, tweets, customer interaction, etc.) - on economically valuable classification tasks (someone inherently cares about the task) - in a setting that mirrors deployment (50 examples per task, info retrieval allowed,
| Author / organization | ought |
|---|---|
| License (as declared) | other |
| Downloads | 2.5K (as reported by Hugging Face) |
| Likes | 66 |
| Created | 2 March 2022 |
| Last updated at source | 25 October 2022 |
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