no code implementations • EMNLP 2020 • Jinyue Feng, Chantal Shaib, Frank Rudzicz
Clinical prediction models often use structured variables and provide outcomes that are not readily interpretable by clinicians.
no code implementations • 1 Mar 2024 • Chantal Shaib, Joe Barrow, Jiuding Sun, Alexa F. Siu, Byron C. Wallace, Ani Nenkova
The applicability of scores extends beyond analysis of generative models; for example, we highlight applications on instruction-tuning datasets and human-produced texts.
no code implementations • 28 Feb 2024 • Chantal Shaib, Joe Barrow, Alexa F. Siu, Byron C. Wallace, Ani Nenkova
Modern instruction-tuned models have become highly capable in text generation tasks such as summarization, and are expected to be released at a steady pace.
1 code implementation • 20 Jun 2023 • Jiuding Sun, Chantal Shaib, Byron C. Wallace
To answer the former, we collect a set of 319 instructions manually written by NLP practitioners for over 80 unique tasks included in widely used benchmarks, and we evaluate the variance and average performance of these instructions as compared to instruction phrasings observed during instruction fine-tuning.
1 code implementation • 10 May 2023 • Chantal Shaib, Millicent L. Li, Sebastian Joseph, Iain J. Marshall, Junyi Jessy Li, Byron C. Wallace
Large language models, particularly GPT-3, are able to produce high quality summaries of general domain news articles in few- and zero-shot settings.