ROBBIE: Robust Bias Evaluation of Large Generative Language Models. - David Esiobu; Xiaoqing Ellen Tan; Saghar Hosseini; Megan Ung; Yuchen Zhang; Jude Fernandes; Jane Dwivedi-Yu; Eleonora Presani; Adina Williams; Eric Michael Smith (EMNLP, 2023)

A Theory on Adam Instability in Large-Scale Machine Learning. - Igor Molybog; Peter Albert; Moya Chen; Zachary DeVito; David Esiobu; Naman Goyal 001; Punit Singh Koura; Sharan Narang; Andrew Poulton; Ruan Silva; Binh Tang; Diana Liskovich; et al. (CoRR, 2023)

Llama 2: Open Foundation and Fine-Tuned Chat Models. - Hugo Touvron; Louis Martin; Kevin Stone; Peter Albert; Amjad Almahairi; Yasmine Babaei; Nikolay Bashlykov; Soumya Batra; Prajjwal Bhargava; Shruti Bhosale; Dan Bikel; Lukas Blecher; et al. (CoRR, 2023)

The Llama 3 Herd of Models. - Abhimanyu Dubey; Abhinav Jauhri; Abhinav Pandey; Abhishek Kadian; Ahmad Al-Dahle; Aiesha Letman; Akhil Mathur; Alan Schelten; Amy Yang; Angela Fan; Anirudh Goyal; Anthony Hartshorn; et al. (CoRR, 2024)

Evaluation data contamination in LLMs: how do we measure it and (when) does it matter? - Aaditya K. Singh; Muhammed Yusuf Kocyigit; Andrew Poulton; David Esiobu; Maria Lomeli; Gergely Szilvasy; Dieuwke Hupkes (CoRR, 2024)

Lost in Inference: Rediscovering the Role of Natural Language Inference for Large Language Models. - Lovish Madaan; David Esiobu; Pontus Stenetorp; Barbara Plank; Dieuwke Hupkes (NAACL (Long Papers), 2025)