xView: Objects in Context in Overhead Imagery. - Darius Lam; Richard Kuzma; Kevin McGee; Samuel Dooley; Michael Laielli; Matthew Klaric; Yaroslav Bulatov; Brendan McCord (CoRR, 2018)

Overhead Detection: Beyond 8-bits and RGB. - Eliza Mace; Keith Manville; Monica Barbu-McInnis; Michael Laielli; Matthew Klaric; Samuel Dooley (CoRR, 2018)

Can an Algorithm be My Healthcare Proxy? - Duncan C. McElfresh; Samuel Dooley; Yuan Cui; Kendra Griesman; Weiqin Wang; Tyler Will; Neil Sehgal; John P. Dickerson (CoRR, 2020)

The Affiliate Matching Problem: On Labor Markets where Firms are Also Interested in the Placement of Previous Workers. - Samuel Dooley; John P. Dickerson (CoRR, 2020)

ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning. - Kevin Kuo; Anthony Ostuni; Elizabeth Horishny; Michael J. Curry; Samuel Dooley; Ping-yeh Chiang; Tom Goldstein; John P. Dickerson (CoRR, 2020)

Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning. - Vedant Nanda; Samuel Dooley; Sahil Singla 002; Soheil Feizi; John P. Dickerson (FAccT, 2021)

PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning. - Neehar Peri; Michael J. Curry; Samuel Dooley; John Dickerson 001 (NeurIPS, 2021)

Robustness Disparities in Commercial Face Detection. - Samuel Dooley; Tom Goldstein; John P. Dickerson (CoRR, 2021)

Comparing Human and Machine Bias in Face Recognition. - Samuel Dooley; Ryan Downing; George Z. Wei; Nathan Shankar; Bradon Thymes; Gudrun Thorkelsdottir; Tiye Kurtz-Miott; Rachel Mattson; Olufemi Obiwumi; Valeriia Cherepanova; Micah Goldblum; John P. Dickerson; et al. (CoRR, 2021)

Field Evidence of the Effects of Privacy, Data Transparency, and Pro-social Appeals on COVID-19 App Attractiveness. - Samuel Dooley; Dana Turjeman; John P. Dickerson; Elissa M. Redmiles (CHI, 2022)

The Dichotomous Affiliate Stable Matching Problem: Approval-Based Matching with Applicant-Employer Relations. - Marina Knittel; Samuel Dooley; John P. Dickerson (IJCAI, 2022)

Robustness Disparities in Face Detection. - Samuel Dooley; George Z. Wei; Tom Goldstein; John Dickerson 001 (NeurIPS, 2022)

Topological Data Analysis for Word Sense Disambiguation. - Michael Rawson; Samuel Dooley; Mithun Bharadwaj; Rishabh Choudhary (CoRR, 2022)

A Deep Dive into Dataset Imbalance and Bias in Face Identification. - Valeriia Cherepanova; Steven Reich; Samuel Dooley; Hossein Souri; Micah Goldblum; Tom Goldstein (CoRR, 2022)

On the Importance of Architectures and Hyperparameters for Fairness in Face Recognition. - Rhea Sukthanker; Samuel Dooley; John P. Dickerson; Colin White; Frank Hutter; Micah Goldblum (CoRR, 2022)

How Technology Impacts and Compares to Humans in Socially Consequential Arenas. - Samuel Dooley (CoRR, 2022)

Ctrl-Shift: How Privacy Sentiment Changed from 2019 to 2021. - Angelica Goetzen; Samuel Dooley; Elissa M. Redmiles (Proc. Priv. Enhancing Technol., 2022)

A Deep Dive into Dataset Imbalance and Bias in Face Identification. - Valeriia Cherepanova; Steven Reich; Samuel Dooley; Hossein Souri; John P. Dickerson; Micah Goldblum; Tom Goldstein (AIES, 2023)

ForecastPFN: Synthetically-Trained Zero-Shot Forecasting. - Samuel Dooley; Gurnoor Singh Khurana; Chirag Mohapatra; Siddartha V. Naidu; Colin White (NeurIPS, 2023)

Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition. - Samuel Dooley; Rhea Sukthanker; John P. Dickerson; Colin White; Frank Hutter; Micah Goldblum (NeurIPS, 2023)

How Library IT Staff Navigate Privacy and Security Challenges and Responsibilities. - Alan F. Luo; Noel Warford; Samuel Dooley; Rachel Greenstadt; Michelle L. Mazurek; Nora McDonald (USENIX Security Symposium, 2023)

Giraffe: Adventures in Expanding Context Lengths in LLMs. - Arka Pal; Deep Karkhanis; Manley Roberts; Samuel Dooley; Arvind Sundararajan; Siddartha Naidu (CoRR, 2023)

Data Contamination Through the Lens of Time. - Manley Roberts; Himanshu Thakur; Christine Herlihy; Colin White; Samuel Dooley (CoRR, 2023)

Fairer and More Accurate Tabular Models Through NAS. - Richeek Das; Samuel Dooley (CoRR, 2023)

Expanding Robustness in Responsible AI for Novel Bias Mitigation. - Samuel Dooley (2023)

To the Cutoff... and Beyond? A Longitudinal Perspective on LLM Data Contamination. - Manley Roberts; Himanshu Thakur; Christine Herlihy; Colin White; Samuel Dooley (ICLR, 2024)

Large Language Models Must Be Taught to Know What They Don't Know. - Sanyam Kapoor; Nate Gruver; Manley Roberts; Katie Collins; Arka Pal; Umang Bhatt; Adrian Weller; Samuel Dooley; Micah Goldblum; Andrew Gordon Wilson (NeurIPS, 2024)

Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive. - Arka Pal; Deep Karkhanis; Samuel Dooley; Manley Roberts; Siddartha Naidu; Colin White (CoRR, 2024)

LiveBench: A Challenging, Contamination-Free LLM Benchmark. - Colin White; Samuel Dooley; Manley Roberts; Arka Pal; Benjamin Feuer; Siddhartha Jain 001; Ravid Shwartz-Ziv; Neel Jain; Khalid Saifullah; Siddartha Naidu; Chinmay Hegde; Yann LeCun; et al. (CoRR, 2024)

Style Outweighs Substance: Failure Modes of LLM Judges in Alignment Benchmarking. - Benjamin Feuer; Micah Goldblum; Teresa Datta; Sanjana Nambiar; Raz Besaleli; Samuel Dooley; Max Cembalest; John P. Dickerson (ICLR, 2025)

Multi-objective Differentiable Neural Architecture Search. - Rhea Sanjay Sukthanker; Arber Zela; Benedikt Staffler; Samuel Dooley; Josif Grabocka; Frank Hutter (ICLR, 2025)

LiveBench: A Challenging, Contamination-Limited LLM Benchmark. - Colin White; Samuel Dooley; Manley Roberts; Arka Pal; Benjamin Feuer; Siddhartha Jain 001; Ravid Shwartz-Ziv; Neel Jain; Khalid Saifullah; Sreemanti Dey; Shubh-Agrawal; Sandeep Singh Sandha; et al. (ICLR, 2025)

Transformers Boost the Performance of Decision Trees on Tabular Data across Sample Sizes. - Mayuka Jayawardhana; Renbo Tu; Samuel Dooley; Valeriia Cherepanova; Andrew Gordon Wilson; Frank Hutter; Colin White; Tom Goldstein; Micah Goldblum (CoRR, 2025)