P-values: misunderstood and misused. - Bertie Vidgen; Taha Yasseri (CoRR, 2016)

Detecting weak and strong Islamophobic hate speech on social media. - Bertie Vidgen; Taha Yasseri (CoRR, 2018)

What, When and Where of petitions submitted to the UK Government during a time of chaos. - Bertie Vidgen; Taha Yasseri (CoRR, 2019)

Trajectories of Islamophobic hate amongst far right actors on Twitter. - Bertie Vidgen; Taha Yasseri; Helen Z. Margetts (CoRR, 2019)

Online Abuse and Human Rights: WOAH Satellite Session at RightsCon 2020. - Vinodkumar Prabhakaran; Zeerak Waseem; Seyi Akiwowo; Bertie Vidgen (WOAH, 2020)

Detecting East Asian Prejudice on Social Media. - Bertie Vidgen; Scott Hale; Ella Guest; Helen Z. Margetts; David A. Broniatowski; Zeerak Waseem; Austin Botelho; Matthew Hall; Rebekah Tromble (WOAH, 2020)

Directions in Abusive Language Training Data: Garbage In, Garbage Out. - Bertie Vidgen; Leon Derczynski (CoRR, 2020)

Deciphering Implicit Hate: Evaluating Automated Detection Algorithms for Multimodal Hate. - Austin Botelho; Scott Hale; Bertie Vidgen (ACL/IJCNLP (Findings), 2021)

HateCheck: Functional Tests for Hate Speech Detection Models. - Paul Röttger; Bertie Vidgen; Dong Nguyen 002; Zeerak Waseem; Helen Z. Margetts; Janet B. Pierrehumbert (ACL/IJCNLP (1), 2021)

Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection. - Bertie Vidgen; Tristan Thrush; Zeerak Waseem; Douwe Kiela (ACL/IJCNLP (1), 2021)

An Expert Annotated Dataset for the Detection of Online Misogyny. - Ella Guest; Bertie Vidgen; Alexandros Mittos; Nishanth Sastry; Gareth Tyson; Helen Z. Margetts (EACL, 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)

Introducing CAD: the Contextual Abuse Dataset. - Bertie Vidgen; Dong Nguyen 002; Helen Z. Margetts; Patrícia G. C. Rossini; Rebekah Tromble (NAACL-HLT, 2021)

Tackling Racial Bias in Automated Online Hate Detection: Towards Fair and Accurate Classification of Hateful Online Users Using Geometric Deep Learning. - Zo Ahmed; Bertie Vidgen; Scott A. Hale (CoRR, 2021)

An influencer-based approach to understanding radical right viral tweets. - Laila Sprejer; Helen Z. Margetts; Kleber Oliveira; David O'Sullivan; Bertie Vidgen (CoRR, 2021)

Handling and Presenting Harmful Text in NLP Research. - Hannah Kirk; Abeba Birhane; Bertie Vidgen; Leon Derczynski (EMNLP (Findings), 2022)

Hatemoji: A Test Suite and Adversarially-Generated Dataset for Benchmarking and Detecting Emoji-Based Hate. - Hannah Kirk; Bertie Vidgen; Paul Röttger; Tristan Thrush; Scott Hale (NAACL-HLT, 2022)

Two Contrasting Data Annotation Paradigms for Subjective NLP Tasks. - Paul Röttger; Bertie Vidgen; Dirk Hovy; Janet B. Pierrehumbert (NAACL-HLT, 2022)

Handling and Presenting Harmful Text. - Leon Derczynski; Hannah Rose Kirk; Abeba Birhane; Bertie Vidgen (CoRR, 2022)

Multilingual HateCheck: Functional Tests for Multilingual Hate Speech Detection Models. - Paul Röttger; Haitham Seelawi; Debora Nozza; Zeerak Talat; Bertie Vidgen (CoRR, 2022)

Is More Data Better? Re-thinking the Importance of Efficiency in Abusive Language Detection with Transformers-Based Active Learning. - Hannah Rose Kirk; Bertie Vidgen; Scott A. Hale (CoRR, 2022)

How can we combat online misinformation? A systematic overview of current interventions and their efficacy. - Pica Johansson; Florence Enock; Scott Hale; Bertie Vidgen; Cassidy Bereskin; Helen Z. Margetts; Jonathan Bright (CoRR, 2022)

Tackling racial bias in automated online hate detection: Towards fair and accurate detection of hateful users with geometric deep learning. - Zo Ahmed; Bertie Vidgen; Scott A. Hale (EPJ Data Sci., 2022)

Editorial for Special Issue on Detecting, Understanding and Countering Online Harms. - Arkaitz Zubiaga; Bertie Vidgen; Miriam Fernández; Nishanth Sastry (Online Soc. Networks Media, 2022)

Improving the Detection of Multilingual Online Attacks with Rich Social Media Data from Singapore. - Janosch Haber; Bertie Vidgen; Matthew Chapman; Vibhor Agarwal; Roy Ka-Wei Lee; Yong Keong Yap; Paul Röttger (ACL (1), 2023)

The Past, Present and Better Future of Feedback Learning in Large Language Models for Subjective Human Preferences and Values. - Hannah Kirk; Andrew M. Bean; Bertie Vidgen; Paul Röttger; Scott Hale (EMNLP, 2023)

SemEval-2023 Task 10: Explainable Detection of Online Sexism. - Hannah Kirk; Wenjie Yin; Bertie Vidgen; Paul Röttger (SemEval@ACL, 2023)

Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedback. - Hannah Rose Kirk; Bertie Vidgen; Paul Röttger; Scott A. Hale (CoRR, 2023)

The Empty Signifier Problem: Towards Clearer Paradigms for Operationalising "Alignment" in Large Language Models. - Hannah Rose Kirk; Bertie Vidgen; Paul Röttger; Scott A. Hale (CoRR, 2023)

SimpleSafetyTests: a Test Suite for Identifying Critical Safety Risks in Large Language Models. - Bertie Vidgen; Hannah Rose Kirk; Rebecca Qian; Nino Scherrer; Anand Kannappan; Scott A. Hale; Paul Röttger (CoRR, 2023)

FinanceBench: A New Benchmark for Financial Question Answering. - Pranab Islam; Anand Kannappan; Douwe Kiela; Rebecca Qian; Nino Scherrer; Bertie Vidgen (CoRR, 2023)

Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI. - Francisco Eiras; Aleksandar Petrov; Bertie Vidgen; Christian Schröder de Witt; Fabio Pizzati; Katherine Elkins; Supratik Mukhopadhyay; Adel Bibi; Botos Csaba; Fabro Steibel; Fazl Barez; Genevieve Smith; et al. (ICML, 2024)

Position: TrustLLM: Trustworthiness in Large Language Models. - Yue Huang; Lichao Sun 001; Haoran Wang 005; Siyuan Wu 001; Qihui Zhang; Yuan Li; Chujie Gao; Yixin Huang; Wenhan Lyu; Yixuan Zhang; Xiner Li; Hanchi Sun; et al. (ICML, 2024)

XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models. - Paul Röttger; Hannah Kirk; Bertie Vidgen; Giuseppe Attanasio; Federico Bianchi 001; Dirk Hovy (NAACL-HLT, 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)

Introducing v0.5 of the AI Safety Benchmark from MLCommons. - Bertie Vidgen; Adarsh Agrawal; Ahmed M. Ahmed 004; Victor Akinwande; Namir Al-Nuaimi; Najla Alfaraj; Elie Alhajjar; Lora Aroyo; Trupti Bavalatti; Borhane Blili-Hamelin; Kurt D. Bollacker; Rishi Bomassani; 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)

Near to Mid-term Risks and Opportunities of Open Source Generative AI. - Francisco Eiras; Aleksandar Petrov; Bertie Vidgen; Christian Schröder de Witt; Fabio Pizzati; Katherine Elkins; Supratik Mukhopadhyay; Adel Bibi; Botos Csaba; Fabro Steibel; Fazl Barez; Genevieve Smith; et al. (CoRR, 2024)

WorkBench: a Benchmark Dataset for Agents in a Realistic Workplace Setting. - Olly Styles; Sam Miller 006; Patricio Cerda-Mardini; Tanaya Guha; Victor Sanchez; Bertie Vidgen (CoRR, 2024)

Risks and Opportunities of Open-Source Generative AI. - Francisco Eiras; Aleksandar Petrov; Bertie Vidgen; Christian Schröder de Witt; Fabio Pizzati; Katherine Elkins; Supratik Mukhopadhyay; Adel Bibi; Aaron Purewal; Botos Csaba; Fabro Steibel; Fazel Keshtkar; et al. (CoRR, 2024)

LMUnit: Fine-grained Evaluation with Natural Language Unit Tests. - Jon Saad-Falcon; Rajan Vivek; William Berrios; Nandita Shankar Naik; Matija Franklin; Bertie Vidgen; Amanpreet Singh; Douwe Kiela; Shikib Mehri (CoRR, 2024)

The benefits, risks and bounds of personalizing the alignment of large language models to individuals. - Hannah Rose Kirk; Bertie Vidgen; Paul Röttger; Scott A. Hale (Nat. Mac. Intell., 2024)

The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources. - Shayne Longpre; Stella Biderman; Alon Albalak; Hailey Schoelkopf; Daniel McDuff; Sayash Kapoor; Kevin Klyman; Kyle Lo; Gabriel Ilharco; Nay San; Maribeth Rauh; Aviya Skowron; et al. (Trans. Mach. Learn. Res., 2024)

SafetyPrompts: A Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety. - Paul Röttger; Fabio Pernisi; Bertie Vidgen; Dirk Hovy (AAAI, 2025)

MSTS: A Multimodal Safety Test Suite for Vision-Language Models. - Paul Röttger; Giuseppe Attanasio; Felix Friedrich; Janis Goldzycher; Alicia Parrish; Rishabh Bhardwaj; Chiara Di Bonaventura; Roman Eng; Gaia El Khoury Geagea; Subhra S. Goswami; Jieun Han; Dirk Hovy; et al. (CoRR, 2025)

Why human-AI relationships need socioaffective alignment. - Hannah Rose Kirk; Iason Gabriel; Christopher Summerfield; Bertie Vidgen; Scott A. Hale (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)

Classification is a RAG problem: A case study on hate speech detection. - Richard Willats; Josh Pennington; Aravind Mohan; Bertie Vidgen (CoRR, 2025)