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2020 – today
- 2024
[c10]Manley Roberts, Himanshu Thakur, Christine Herlihy, Colin White, Samuel Dooley:
To the Cutoff... and Beyond? A Longitudinal Perspective on LLM Data Contamination. ICLR 2024- [i25]Arka Pal, Deep Karkhanis, Samuel Dooley, Manley Roberts, Siddartha Naidu, Colin White:
Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive. CoRR abs/2402.13228 (2024) - [i24]Rhea Sanjay Sukthanker, Arber Zela, Benedikt Staffler, Samuel Dooley, Josif Grabocka, Frank Hutter:
Multi-objective Differentiable Neural Architecture Search. CoRR abs/2402.18213 (2024) - [i23]Sanyam Kapoor, Nate Gruver, Manley Roberts, Katherine M. Collins, Arka Pal, Umang Bhatt, Adrian Weller, Samuel Dooley, Micah Goldblum, Andrew Gordon Wilson:
Large Language Models Must Be Taught to Know What They Don't Know. CoRR abs/2406.08391 (2024) - [i22]Colin White, Samuel Dooley, Manley Roberts, Arka Pal, Benjamin Feuer, Siddhartha Jain, Ravid Shwartz-Ziv, Neel Jain, Khalid Saifullah, Siddartha Naidu, Chinmay Hegde, Yann LeCun, Tom Goldstein, Willie Neiswanger, Micah Goldblum:
LiveBench: A Challenging, Contamination-Free LLM Benchmark. CoRR abs/2406.19314 (2024) - [i21]Benjamin Feuer, Micah Goldblum, Teresa Datta, Sanjana Nambiar, Raz Besaleli, Samuel Dooley, Max Cembalest, John P. Dickerson:
Style Outweighs Substance: Failure Modes of LLM Judges in Alignment Benchmarking. CoRR abs/2409.15268 (2024) - 2023
- [b1]Samuel Dooley:
Expanding Robustness in Responsible AI for Novel Bias Mitigation. University of Maryland, College Park, MD, USA, 2023 - [c9]Valeriia Cherepanova
, Steven Reich, Samuel Dooley, Hossein Souri, John P. Dickerson, Micah Goldblum, Tom Goldstein:
A Deep Dive into Dataset Imbalance and Bias in Face Identification. AIES 2023: 229-247 - [c8]Samuel Dooley, Gurnoor Singh Khurana, Chirag Mohapatra, Siddartha V. Naidu, Colin White:
ForecastPFN: Synthetically-Trained Zero-Shot Forecasting. NeurIPS 2023 - [c7]Samuel Dooley, Rhea Sukthanker, John P. Dickerson, Colin White, Frank Hutter, Micah Goldblum:
Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition. NeurIPS 2023 - [c6]Alan F. Luo, Noel Warford, Samuel Dooley, Rachel Greenstadt, Michelle L. Mazurek, Nora McDonald:
How Library IT Staff Navigate Privacy and Security Challenges and Responsibilities. USENIX Security Symposium 2023: 5647-5664 - [i20]Arka Pal, Deep Karkhanis, Manley Roberts, Samuel Dooley, Arvind Sundararajan, Siddartha Naidu:
Giraffe: Adventures in Expanding Context Lengths in LLMs. CoRR abs/2308.10882 (2023) - [i19]Manley Roberts, Himanshu Thakur, Christine Herlihy, Colin White, Samuel Dooley:
Data Contamination Through the Lens of Time. CoRR abs/2310.10628 (2023) - [i18]Richeek Das, Samuel Dooley:
Fairer and More Accurate Tabular Models Through NAS. CoRR abs/2310.12145 (2023) - [i17]Samuel Dooley, Gurnoor Singh Khurana, Chirag Mohapatra, Siddartha Naidu, Colin White:
ForecastPFN: Synthetically-Trained Zero-Shot Forecasting. CoRR abs/2311.01933 (2023) - 2022
- [j1]Angelica Goetzen, Samuel Dooley, Elissa M. Redmiles:
Ctrl-Shift: How Privacy Sentiment Changed from 2019 to 2021. Proc. Priv. Enhancing Technol. 2022(4): 457-485 (2022) - [c5]Samuel Dooley, Dana Turjeman, John P. Dickerson, Elissa M. Redmiles:
Field Evidence of the Effects of Privacy, Data Transparency, and Pro-social Appeals on COVID-19 App Attractiveness. CHI 2022: 622:1-622:21 - [c4]Marina Knittel, Samuel Dooley, John P. Dickerson:
The Dichotomous Affiliate Stable Matching Problem: Approval-Based Matching with Applicant-Employer Relations. IJCAI 2022: 356-362 - [c3]Samuel Dooley, George Z. Wei, Tom Goldstein, John Dickerson:
Robustness Disparities in Face Detection. NeurIPS 2022 - [i16]Marina Knittel, Samuel Dooley, John P. Dickerson:
The Dichotomous Affiliate Stable Matching Problem: Approval-Based Matching with Applicant-Employer Relations. CoRR abs/2202.11095 (2022) - [i15]Michael Rawson, Samuel Dooley, Mithun Bharadwaj, Rishabh Choudhary:
Topological Data Analysis for Word Sense Disambiguation. CoRR abs/2203.00565 (2022) - [i14]Valeriia Cherepanova, Steven Reich, Samuel Dooley, Hossein Souri, Micah Goldblum, Tom Goldstein:
A Deep Dive into Dataset Imbalance and Bias in Face Identification. CoRR abs/2203.08235 (2022) - [i13]Rhea Sukthanker, Samuel Dooley, John P. Dickerson, Colin White, Frank Hutter, Micah Goldblum:
On the Importance of Architectures and Hyperparameters for Fairness in Face Recognition. CoRR abs/2210.09943 (2022) - [i12]Samuel Dooley:
How Technology Impacts and Compares to Humans in Socially Consequential Arenas. CoRR abs/2211.03554 (2022) - [i11]Samuel Dooley, George Z. Wei, Tom Goldstein, John P. Dickerson:
Robustness Disparities in Face Detection. CoRR abs/2211.15937 (2022) - 2021
- [c2]Vedant Nanda, Samuel Dooley, Sahil Singla, Soheil Feizi, John P. Dickerson:
Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning. FAccT 2021: 466-477 - [c1]Neehar Peri, Michael J. Curry, Samuel Dooley, John Dickerson:
PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning. NeurIPS 2021: 17532-17542 - [i10]Neehar Peri, Michael J. Curry, Samuel Dooley, John P. Dickerson:
PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning. CoRR abs/2106.03215 (2021) - [i9]Samuel Dooley, Tom Goldstein, John P. Dickerson:
Robustness Disparities in Commercial Face Detection. CoRR abs/2108.12508 (2021) - [i8]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, Tom Goldstein:
Comparing Human and Machine Bias in Face Recognition. CoRR abs/2110.08396 (2021) - [i7]Angelica Goetzen, Samuel Dooley, Elissa M. Redmiles:
Ctrl-Shift: How Privacy Sentiment Changed from 2019 to 2021. CoRR abs/2110.09437 (2021) - 2020
- [i6]Duncan C. McElfresh, Samuel Dooley, Yuan Cui, Kendra Griesman, Weiqin Wang, Tyler Will, Neil Sehgal, John P. Dickerson:
Can an Algorithm be My Healthcare Proxy? CoRR abs/2001.09742 (2020) - [i5]Vedant Nanda, Samuel Dooley, Sahil Singla, Soheil Feizi, John P. Dickerson:
Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning. CoRR abs/2006.12621 (2020) - [i4]Samuel Dooley, John P. Dickerson:
The Affiliate Matching Problem: On Labor Markets where Firms are Also Interested in the Placement of Previous Workers. CoRR abs/2009.11867 (2020) - [i3]Kevin Kuo, Anthony Ostuni, Elizabeth Horishny, Michael J. Curry, Samuel Dooley, Ping-yeh Chiang, Tom Goldstein, John P. Dickerson:
ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning. CoRR abs/2010.06398 (2020)
2010 – 2019
- 2018
- [i2]Darius Lam, Richard Kuzma, Kevin McGee, Samuel Dooley, Michael Laielli, Matthew Klaric, Yaroslav Bulatov, Brendan McCord:
xView: Objects in Context in Overhead Imagery. CoRR abs/1802.07856 (2018) - [i1]Eliza Mace, Keith Manville, Monica Barbu-McInnis, Michael Laielli, Matthew Klaric, Samuel Dooley:
Overhead Detection: Beyond 8-bits and RGB. CoRR abs/1808.02443 (2018)
Coauthor Index
aka: John P. Dickerson
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last updated on 2024-10-16 20:33 CEST by the dblp team
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