The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics. - Sebastian Gehrmann; Tosin P. Adewumi; Karmanya Aggarwal; Pawan Sasanka Ammanamanchi; Aremu Anuoluwapo; Antoine Bosselut; Khyathi Raghavi Chandu; Miruna-Adriana Clinciu; Dipanjan Das 001; Kaustubh D. Dhole; Wanyu Du; Esin Durmus; et al. (CoRR, 2021)

Reusable Templates and Guides For Documenting Datasets and Models for Natural Language Processing and Generation: A Case Study of the HuggingFace and GEM Data and Model Cards. - Angelina McMillan-Major; Salomey Osei; Juan Diego Rodriguez; Pawan Sasanka Ammanamanchi; Sebastian Gehrmann; Yacine Jernite (CoRR, 2021)

GEMv2: Multilingual NLG Benchmarking in a Single Line of Code. - Sebastian Gehrmann; Abhik Bhattacharjee; Abinaya Mahendiran; Alex Wang; Alexandros Papangelis; Aman Madaan; Angelina McMillan-Major; Anna Shvets; Ashish Upadhyay; Bingsheng Yao; Bryan Wilie; Chandra Bhagavatula; et al. (CoRR, 2022)

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model. - Teven Le Scao; Angela Fan; Christopher Akiki; Ellie Pavlick; Suzana Ilic; Daniel Hesslow; Roman Castagné; Alexandra Sasha Luccioni; François Yvon; Matthias Gallé; Jonathan Tow; Alexander M. Rush; et al. (CoRR, 2022)

Stay on topic with Classifier-Free Guidance. - Guillaume Sanchez; Honglu Fan; Alexander Spangher; Elad Levi; Pawan Sasanka Ammanamanchi; Stella Biderman (CoRR, 2023)

Lessons from the Trenches on Reproducible Evaluation of Language Models. - Stella Biderman; Hailey Schoelkopf; Lintang Sutawika; Leo Gao; Jonathan Tow; Baber Abbasi; Alham Fikri Aji; Pawan Sasanka Ammanamanchi; Sidney Black; Jordan Clive; Anthony DiPofi; Julen Etxaniz; et al. (CoRR, 2024)

Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models. - Alex Havrilla; Andrew Dai 001; Laura O'Mahony; Koen Oostermeijer; Vera Zisler; Alon Albalak; Fabrizio Milo; Sharath Chandra Raparthy; Kanishk Gandhi; Baber Abbasi; Duy Phung; Maia Iyer; et al. (CoRR, 2024)