563 citations · 597 across the 13 of their papers we have counts for
4 papers · 1 filter
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
BigScience Workshop, :, Teven Le Scao +391
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…
Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind
Mo Yu, Qiujing Wang, Shunchi Zhang +8
When reading a story, humans can quickly understand new fictional characters with a few observations, mainly by drawing analogies to fictional and real people they already know. Th…
Automatic Multi-Label Prompting: Simple and Interpretable Few-Shot Classification
Han Wang, Canwen Xu, Julian McAuley
Prompt-based learning (i.e., prompting) is an emerging paradigm for exploiting knowledge learned by a pretrained language model. In this paper, we propose Automatic Multi-Label Pro…
PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts
Stephen H. Bach, Victor Sanh, Zheng-Xin Yong +24
PromptSource is a system for creating, sharing, and using natural language prompts. Prompts are functions that map an example from a dataset to a natural language input and target…