Interpretation of Natural Language Rules in Conversational Machine Reading. - Marzieh Saeidi; Max Bartolo; Patrick Lewis 001; Sameer Singh 001; Tim Rocktäschel; Mike Sheldon; Guillaume Bouchard; Sebastian Riedel 001 (EMNLP, 2018)

Pre-trained Contextual Embeddings for Litigation Code Classification. - Max Bartolo; Kamil Tylinski; Alastair Moore (LegalAIIA@ICAIL, 2019)

Undersensitivity in Neural Reading Comprehension. - Johannes Welbl; Pasquale Minervini; Max Bartolo; Pontus Stenetorp; Sebastian Riedel 001 (EMNLP (Findings), 2020)

Beat the AI: Investigating Adversarial Human Annotations for Reading Comprehension. - Max Bartolo; Alastair Roberts; Johannes Welbl; Sebastian Riedel 001; Pontus Stenetorp (CoRR, 2020)

Beat the AI: Investigating Adversarial Human Annotation for Reading Comprehension. - Max Bartolo; Alastair Roberts; Johannes Welbl; Sebastian Riedel 001; Pontus Stenetorp (Trans. Assoc. Comput. Linguistics, 2020)

Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation. - Max Bartolo; Tristan Thrush; Robin Jia; Sebastian Riedel 001; Pontus Stenetorp; Douwe Kiela (EMNLP (1), 2021)

Contrasting Human- and Machine-Generated Word-Level Adversarial Examples for Text Classification. - Maximilian Mozes; Max Bartolo; Pontus Stenetorp; Bennett Kleinberg; Lewis D. Griffin (EMNLP (1), 2021)

Dynabench: Rethinking Benchmarking in NLP. - Douwe Kiela; Max Bartolo; Yixin Nie; Divyansh Kaushik; Atticus Geiger; Zhengxuan Wu; Bertie Vidgen; Grusha Prasad; Amanpreet Singh; Pratik Ringshia; Zhiyi Ma; Tristan Thrush; et al. (NAACL-HLT, 2021)

Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity. - Yao Lu; Max Bartolo; Alastair Moore; Sebastian Riedel 001; Pontus Stenetorp (ACL (1), 2022)

Dynatask: A Framework for Creating Dynamic AI Benchmark Tasks. - Tristan Thrush; Kushal Tirumala; Anmol Gupta; Max Bartolo; Pedro Rodriguez 001; Tariq Kane; William Gaviria Rojas; Peter Mattson; Adina Williams; Douwe Kiela (ACL (demo), 2022)

Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality. - Tristan Thrush; Ryan Jiang; Max Bartolo; Amanpreet Singh; Adina Williams; Douwe Kiela; Candace Ross (CVPR, 2022)

Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistants. - Max Bartolo; Tristan Thrush; Sebastian Riedel 001; Pontus Stenetorp; Robin Jia; Douwe Kiela (NAACL-HLT, 2022)

DataPerf: Benchmarks for Data-Centric AI Development. - Mark Mazumder; Colby R. Banbury; Xiaozhe Yao; Bojan Karlas; William Gaviria Rojas; Sudnya Frederick Diamos; Greg Diamos; Lynn He; Alicia Parrish; Hannah Rose Kirk; Jessica Quaye; Charvi Rastogi; et al. (NeurIPS, 2023)

Adversarial Nibbler: A Data-Centric Challenge for Improving the Safety of Text-to-Image Models. - Alicia Parrish; Hannah Rose Kirk; Jessica Quaye; Charvi Rastogi; Max Bartolo; Oana Inel; Juan Ciro; Rafael Mosquera; Addison Howard; Will Cukierski; D. Sculley; Vijay Janapa Reddi; et al. (CoRR, 2023)

DMLR: Data-centric Machine Learning Research - Past, Present and Future. - Luis Oala; Manil Maskey; Lilith Bat-Leah; Alicia Parrish; Nezihe Merve Gürel; Tzu-Sheng Kuo; Yang Liu 018; Rotem Dror; Danilo Brajovic; Xiaozhe Yao; Max Bartolo; William Gaviria Rojas; et al. (CoRR, 2023)

Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning. - Shivalika Singh; Freddie Vargus; Daniel D'souza; Börje Karlsson 001; Abinaya Mahendiran; Wei-Yin Ko; Herumb Shandilya; Jay Patel; Deividas Mataciunas; Laura O'Mahony; Mike Zhang; Ramith Hettiarachchi; et al. (ACL (1), 2024)

Fishing for Magikarp: Automatically Detecting Under-trained Tokens in Large Language Models. - Sander Land; Max Bartolo (EMNLP, 2024)

Adversarial Nibbler: An Open Red-Teaming Method for Identifying Diverse Harms in Text-to-Image Generation. - Jessica Quaye; Alicia Parrish; Oana Inel; Charvi Rastogi; Hannah Rose Kirk; Minsuk Kahng; Erin van Liemt; Max Bartolo; Jess Tsang; Justin White; Nathan Clement; Rafael Mosquera; et al. (FAccT, 2024)

Human Feedback is not Gold Standard. - Tom Hosking; Phil Blunsom; Max Bartolo (ICLR, 2024)

The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models. - Hannah Rose Kirk; Alexander Whitefield; Paul Röttger; Andrew M. Bean; Katerina Margatina; Rafael Mosquera Gómez; Juan Ciro; Max Bartolo; Adina Williams; He He 001; Bertie Vidgen; Scott Hale (NeurIPS, 2024)

Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning. - Shivalika Singh; Freddie Vargus; Daniel D'souza; Börje F. Karlsson; Abinaya Mahendiran; Wei-Yin Ko; Herumb Shandilya; Jay Patel; Deividas Mataciunas; Laura O'Mahony; Mike Zhang; Ramith Hettiarachchi; et al. (CoRR, 2024)

The PRISM Alignment Project: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models. - Hannah Rose Kirk; Alexander Whitefield; Paul Röttger; Andrew M. Bean; Katerina Margatina; Juan Ciro; Rafael Mosquera; Max Bartolo; Adina Williams; He He 001; Bertie Vidgen; Scott A. Hale (CoRR, 2024)

Aya 23: Open Weight Releases to Further Multilingual Progress. - Viraat Aryabumi; John Dang; Dwarak Talupuru; Saurabh Dash; David Cairuz; Hangyu Lin; Bharat Venkitesh; Madeline Smith; Jon Ander Campos; Yi Chern Tan; Kelly Marchisio; Max Bartolo; et al. (CoRR, 2024)

Understanding Likelihood Over-optimisation in Direct Alignment Algorithms. - Zhengyan Shi; Sander Land; Acyr Locatelli; Matthieu Geist; Max Bartolo (CoRR, 2024)

Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models. - Laura Ruis; Maximilian Mozes; Juhan Bae; Siddhartha Rao Kamalakara; Dwarak Talupuru; Acyr Locatelli; Robert Kirk; Tim Rocktäschel; Edward Grefenstette; Max Bartolo (CoRR, 2024)

Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models. - Laura Ruis; Maximilian Mozes; Juhan Bae; Siddhartha Rao Kamalakara; Dwaraknath Gnaneshwar; Acyr Locatelli; Robert Kirk; Tim Rocktäschel; Edward Grefenstette; Max Bartolo (ICLR, 2025)

Improving Reward Models with Synthetic Critiques. - Zihuiwen Ye; Fraser Greenlee-Scott; Max Bartolo; Phil Blunsom; Jon Ander Campos; Matthias Gallé (NAACL (Findings), 2025)

Atla Selene Mini: A General Purpose Evaluation Model. - Andrei Alexandru; Antonia Calvi; Henry Broomfield; Jackson Golden; Kyle Dai; Mathias Leys; Maurice Burger; Max Bartolo; Roman Engeler; Sashank Pisupati; Toby Drane; Young Sun Park (CoRR, 2025)

LLMs can implicitly learn from mistakes in-context. - Lisa Alazraki; Maximilian Mozes; Jon Ander Campos; Yi Chern Tan; Marek Rei; Max Bartolo (CoRR, 2025)

AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons. - Shaona Ghosh; Heather Frase; Adina Williams; Sarah Luger; Paul Röttger; Fazl Barez; Sean McGregor; Kenneth Fricklas; Mala Kumar; Quentin Feuillade-Montixi; Kurt Bollacker; Felix Friedrich; et al. (CoRR, 2025)

Command A: An Enterprise-Ready Large Language Model. - Aakanksha; Arash Ahmadian; Marwan Ahmed; Jay Alammar; Milad Alizadeh; Yazeed Alnumay; Sophia Althammer; Arkady Arkhangorodsky; Viraat Aryabumi; Dennis Aumiller; Raphaël Avalos; Zahara Aviv; et al. (CoRR, 2025)

Reverse Engineering Human Preferences with Reinforcement Learning. - Lisa Alazraki; Yi Chern Tan; Jon Ander Campos; Maximilian Mozes; Marek Rei; Max Bartolo (CoRR, 2025)