12 citations · 23 across the 2 of their papers we have counts for
4 papers
Efficient Reasoning Training Does Not Always Harm CoT Faithfulness and Monitorability
Samuel Lewis-Lim, Xingwei Tan, Mario Sanger +2
Chain-of-thought (CoT) reasoning allows humans to inspect how large language models reach their answers, and oversee model behaviour. This reasoning comes at an increased inference…
Large Language Models to the Rescue: Reducing the Complexity in Scientific Workflow Development Using ChatGPT
Mario Sänger, Ninon De Mecquenem, Katarzyna Ewa Lewińska +4
Scientific workflow systems are increasingly popular for expressing and executing complex data analysis pipelines over large datasets, as they offer reproducibility, dependability,…
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…
BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing
Jason Alan Fries, Leon Weber, Natasha Seelam +40
Training and evaluating language models increasingly requires the construction of meta-datasets --diverse collections of curated data with clear provenance. Natural language prompt…