Lucas Dixon

Lucas Dixon

Lucas is a principal research scientist in Google DeepMind and co-lead of PAIR (People and AI Research). He works on visualisation, interpretability and control of machine learning systems, and specifically language models. His work explores how people can productively and fairly benefit from machine learning systems.

Previously, he was Chief Scientist at Jigsaw where he founded engineering and research. He has contributed scientific advances and systems in multiple disciplines including digital security, formal logic, machine learning, and data visualization. For example he co-founded uProxy & Outline, Project Shield, DigitalAttackMap; Syria Defection Tracker, unfiltered.news, Conversation AI and Perspective API.

Before Google, Lucas completed his PhD and worked at the University of Edinburgh on the automation of mathematical reasoning and graphical languages applied to quantum information. He also helped run a non-profit working towards more rational and informed discussion and decision making, and was a co-founder of TheoryMine - a playful take on automating mathematical discovery. Outside of scientific advances, Lucas is also a martial arts instructor in Paris.

Research Areas

Authored Publications
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    LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models
    Minsuk Kahng
    Ian Tenney
    Mahima Pushkarna
    Michael Xieyang Liu
    James Wexler
    Emily Reif
    Krystal Kallarackal
    Minsuk Chang
    Michael Terry
    Lucas Dixon
    Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA '24), ACM (2024)
    "We Need Structured Output": Towards User-centered Constraints on Large Language Model Output
    Michael Xieyang Liu
    Frederick Liu
    Alex Fiannaca
    Terry Koo
    Lucas Dixon
    Michael Terry
    Carrie Cai
    In Extended Abstract in ACM CHI Conference on Human Factors in Computing Systems (CHI EA '24), ACM (2024), pp. 9 (to appear)
    Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences
    Scott Sanner
    Krisztian Balog
    Filip Radlinski
    Ben Wedin
    Lucas Dixon
    Proceedings of ACM Conference on Recommender Systems (RecSys ’23) (2023) (to appear)
    Sparsely Activated Language Models are Efficient In-Context Learners
    Adams Yu
    Andrew Dai
    Barret Richard Zoph
    Claire Cui
    Dmitry (Dima) Lepikhin
    Emma Wang
    Kathy Meier-Hellstern
    Kellie Webster
    Kevin Robinson
    Kun Zhang
    Liam B. Fedus
    Lucas Dixon
    Maarten Paul Bosma
    Marie Pellat
    Maxim Krikun
    Nan Du
    Orhan Firat
    Quoc V. Le
    Simon Tong
    Tao Wang
    Toju Duke
    Yanping Huang
    Yanqi Zhou
    Yonghui Wu
    Yuanzhong Xu
    Zhifeng Chen
    Zongwei Zhou
    (2022)
    On Natural Language User Profiles for Transparent and Scrutable Recommendation
    Filip Radlinski
    Krisztian Balog
    Fernando Diaz
    Lucas Gill Dixon
    Ben Wedin
    Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '22) (2022)
    Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis
    Shayegan Omidshafiei
    Andrei Kapishnikov
    Yannick Assogba
    Lucas Gill Dixon
    Been Kim
    Advances in Neural Information Processing Systems (NeurIPS) (2022) (to appear)
    Context Sensitivity Estimation in Toxicity Detection
    Alexandros Xenos
    Ioannis Pavlopoulos
    Ion Androutsopoulos
    Jeffrey Scott Sorensen
    Lucas Gill Dixon
    First Monday (2022)
    Context-Sensitivity Estimation in Toxicity Classification
    Ioannis Pavlopoulos
    Ion Androutsopoulos
    Jeffrey Scott Sorensen
    Lucas Gill Dixon
    ACL-IJCNLP 2021: (2021)
    Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification
    Daniel Borkan
    Jeffrey Sorensen
    Lucas Dixon
    Lucy Vasserman
    Nithum Thain
    ACM Conference on Fairness, Accountability, and Transparency (2019) (to appear)
    Conversations Gone Awry: Detecting Warning Signs of Conversational Failure
    Justine Zhang
    Jonathan P. Chang
    Cristian Danescu-Niculescu-Mizil
    Lucas Dixon
    Nithum Thain
    Dario Taraborelli
    Proceedings of ACL, ACM Digital Library (2018)
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