The Winograd Schema Challenge and Reasoning about Correlation. - Daniel Bailey; Amelia J. Harrison; Yuliya Lierler; Vladimir Lifschitz; Julian Michael (AAAI Spring Symposia, 2015)

Human-in-the-Loop Parsing. - Luheng He; Julian Michael; Mike Lewis; Luke Zettlemoyer (EMNLP, 2016)

Proving infinitary formulas. - Amelia Harrison; Vladimir Lifschitz; Julian Michael (Theory Pract. Log. Program., 2016)

Large-Scale QA-SRL Parsing. - Nicholas FitzGerald; Julian Michael; Luheng He; Luke Zettlemoyer (ACL (1), 2018)

GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding. - Alex Wang; Amanpreet Singh; Julian Michael; Felix Hill; Omer Levy; Samuel R. Bowman (BlackboxNLP@EMNLP, 2018)

Crowdsourcing Question-Answer Meaning Representations. - Julian Michael; Gabriel Stanovsky; Luheng He; Ido Dagan; Luke Zettlemoyer (NAACL-HLT (2), 2018)

Supervised Open Information Extraction. - Gabriel Stanovsky; Julian Michael; Luke Zettlemoyer; Ido Dagan (NAACL-HLT, 2018)

SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems. - Alex Wang; Yada Pruksachatkun; Nikita Nangia; Amanpreet Singh; Julian Michael; Felix Hill; Omer Levy; Samuel R. Bowman (NeurIPS, 2019)

Crowdsourcing a High-Quality Gold Standard for QA-SRL. - Paul Roit; Ayal Klein; Daniela Stepanov; Jonathan Mamou; Julian Michael; Gabriel Stanovsky; Luke Zettlemoyer; Ido Dagan (CoRR, 2019)

Controlled Crowdsourcing for High-Quality QA-SRL Annotation. - Paul Roit; Ayal Klein; Daniela Stepanov; Jonathan Mamou; Julian Michael; Gabriel Stanovsky; Luke Zettlemoyer; Ido Dagan (ACL, 2020)

Asking without Telling: Exploring Latent Ontologies in Contextual Representations. - Julian Michael; Jan A. Botha; Ian Tenney (EMNLP (1), 2020)

AmbigQA: Answering Ambiguous Open-domain Questions. - Sewon Min; Julian Michael; Hannaneh Hajishirzi; Luke Zettlemoyer (EMNLP (1), 2020)

Inducing Semantic Roles Without Syntax. - Julian Michael; Luke Zettlemoyer (ACL/IJCNLP (Findings), 2021)

Prompting Contrastive Explanations for Commonsense Reasoning Tasks. - Bhargavi Paranjape; Julian Michael; Marjan Ghazvininejad; Hannaneh Hajishirzi; Luke Zettlemoyer (ACL/IJCNLP (Findings), 2021)

Asking It All: Generating Contextualized Questions for any Semantic Role. - Valentina Pyatkin; Paul Roit; Julian Michael; Yoav Goldberg; Reut Tsarfaty; Ido Dagan (EMNLP (1), 2021)

Nearest Neighbor Zero-Shot Inference. - Weijia Shi; Julian Michael; Suchin Gururangan; Luke Zettlemoyer (EMNLP, 2022)

What Do NLP Researchers Believe? Results of the NLP Community Metasurvey. - Julian Michael; Ari Holtzman; Alicia Parrish; Aaron Mueller; Alex Wang; Angelica Chen; Divyam Madaan; Nikita Nangia; Richard Yuanzhe Pang; Jason Phang; Samuel R. Bowman (ACL (1), 2023)

We're Afraid Language Models Aren't Modeling Ambiguity. - Alisa Liu; Zhaofeng Wu; Julian Michael; Alane Suhr; Peter West; Alexander Koller; Swabha Swayamdipta; Noah A. Smith; Yejin Choi 001 (EMNLP, 2023)

Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting. - Miles Turpin; Julian Michael; Ethan Perez; Samuel R. Bowman (NeurIPS, 2023)

Debate Helps Supervise Unreliable Experts. - Julian Michael; Salsabila Mahdi; David Rein; Jackson Petty; Julien Dirani; Vishakh Padmakumar; Samuel R. Bowman (CoRR, 2023)

GPQA: A Graduate-Level Google-Proof Q&A Benchmark. - David Rein; Betty Li Hou; Asa Cooper Stickland; Jackson Petty; Richard Yuanzhe Pang; Julien Dirani; Julian Michael; Samuel R. Bowman (CoRR, 2023)

The Case for Scalable, Data-Driven Theory: A Paradigm for Scientific Progress in NLP. - Julian Michael (CoRR, 2023)

Building Blocks for Data-Driven Theories of Language Understanding - Julian Michael (2023)

Analyzing the Role of Semantic Representations in the Era of Large Language Models. - Zhijing Jin 001; Yuen Chen; Fernando Gonzalez Adauto; Jiarui Liu 004; Jiayi Zhang; Julian Michael; Bernhard Schölkopf; Mona T. Diab (NAACL-HLT, 2024)

Bias-Augmented Consistency Training Reduces Biased Reasoning in Chain-of-Thought. - James Chua; Edward Rees; Hunar Batra; Samuel R. Bowman; Julian Michael; Ethan Perez; Miles Turpin (CoRR, 2024)

Analyzing the Role of Semantic Representations in the Era of Large Language Models. - Zhijing Jin 001; Yuen Chen; Fernando Gonzalez; Jiarui Liu 004; Jiayi Zhang; Julian Michael; Bernhard Schölkopf; Mona T. Diab (CoRR, 2024)

Training Language Models to Win Debates with Self-Play Improves Judge Accuracy. - Samuel Arnesen; David Rein; Julian Michael (CoRR, 2024)

Rapid Response: Mitigating LLM Jailbreaks with a Few Examples. - Alwin Peng; Julian Michael; Henry Sleight; Ethan Perez; Mrinank Sharma (CoRR, 2024)

Alignment faking in large language models. - Ryan Greenblatt; Carson Denison; Benjamin Wright; Fabien Roger; Monte MacDiarmid; Samuel Marks; Johannes Treutlein; Tim Belonax; Jack Chen; David Duvenaud; Akbir Khan; Julian Michael; et al. (CoRR, 2024)

International AI Safety Report. - Yoshua Bengio; Sören Mindermann; Daniel Privitera; Tamay Besiroglu; Rishi Bommasani; Stephen Casper; Yejin Choi 001; Philip Fox; Ben Garfinkel; Danielle Goldfarb; Hoda Heidari; Anson Ho; et al. (CoRR, 2025)

AI Debate Aids Assessment of Controversial Claims. - Salman Rahman; Sheriff Issaka; Ashima Suvarna; Genglin Liu; James Shiffer; Jaeyoung Lee; Md. Rizwan Parvez; Hamid Palangi; Shi Feng; Nanyun Peng 001; Yejin Choi 001; Julian Michael; et al. (CoRR, 2025)

A Red Teaming Roadmap Towards System-Level Safety. - Zifan Wang 001; Christina Q. Knight; Jeremy Kritz; Willow Primack; Julian Michael (CoRR, 2025)

FORTRESS: Frontier Risk Evaluation for National Security and Public Safety. - Christina Q. Knight; Kaustubh Deshpande; Ved Sirdeshmukh; Meher Mankikar; Scale Red Team; SEAL Research Team; Julian Michael (CoRR, 2025)

Why Do Some Language Models Fake Alignment While Others Don't? - Abhay Sheshadri; John Hughes; Julian Michael; Alex Mallen; Arun Jose; Janus; Fabien Roger (CoRR, 2025)

The Singapore Consensus on Global AI Safety Research Priorities. - Yoshua Bengio; Tegan Maharaj; Luke Ong; Stuart Russell 001; Dawn Song; Max Tegmark; Lan Xue; Ya-Qin Zhang; Stephen Casper; Wan Sie Lee; Sören Mindermann; Vanessa Wilfred; et al. (CoRR, 2025)

Teaching Models to Verbalize Reward Hacking in Chain-of-Thought Reasoning. - Miles Turpin; Andy Arditi; Marvin Li; Joe Benton; Julian Michael (CoRR, 2025)

Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety. - Tomek Korbak; Mikita Balesni; Elizabeth Barnes; Yoshua Bengio; Joe Benton; Joseph Bloom; Mark Chen 003; Alan Cooney; Allan Dafoe; Anca D. Dragan; Scott Emmons; Owain Evans; et al. (CoRR, 2025)

Inverse Scaling in Test-Time Compute. - Aryo Pradipta Gema; Alexander Hägele; Runjin Chen; Andy Arditi; Jacob Goldman-Wetzler; Kit Fraser-Taliente; Henry Sleight; Linda Petrini; Julian Michael; Beatrice Alex; Pasquale Minervini; Yanda Chen; et al. (CoRR, 2025)

Search-Time Data Contamination. - Ziwen Han; Meher Mankikar; Julian Michael; Zifan Wang (CoRR, 2025)