Valeriia Cherepanova

25 papers A* 6C 1Misc 1Journal 16

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Has My System Prompt Been Used? Large Language Model Prompt Membership Inference. CoRR Roman Levin, Valeriia Cherepanova, Abhimanyu Hans, Avi Schwarzschild, Tom Goldstein
2025	J	`jnl`	Transformers Boost the Performance of Decision Trees on Tabular Data across Sample Sizes. CoRR Mayuka Jayawardhana, Renbo Tu, Samuel Dooley, Valeriia Cherepanova, Andrew Gordon Wilson, Frank Hutter, Colin White, Tom Goldstein, Micah Goldblum
2024	J	`jnl`	Improving LLM Group Fairness on Tabular Data via In-Context Learning. CoRR Valeriia Cherepanova, Chia-Jung Lee, Nil-Jana Akpinar, Riccardo Fogliato, Martín Bertrán, Michael Kearns, James Zou
2024	A*	`conf`	Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text. ICML Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, Hamid Kazemi, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
2024	J	`jnl`	Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text. CoRR Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, Hamid Kazemi, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
2024	J	`jnl`	Talking Nonsense: Probing Large Language Models' Understanding of Adversarial Gibberish Inputs. CoRR Valeriia Cherepanova, James Zou
2024	A*	`conf`	TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks. NeurIPS Benjamin Feuer, Robin Schirrmeister, Valeriia Cherepanova, Chinmay Hegde, Frank Hutter, Micah Goldblum, Niv Cohen, Colin White
2024	J	`jnl`	TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks. CoRR Benjamin Feuer, Robin Tibor Schirrmeister, Valeriia Cherepanova, Chinmay Hegde, Frank Hutter, Micah Goldblum, Niv Cohen, Colin White
2023	C	`conf`	A Deep Dive into Dataset Imbalance and Bias in Face Identification. AIES Valeriia Cherepanova, Steven Reich, Samuel Dooley, Hossein Souri, John P. Dickerson, Micah Goldblum, Tom Goldstein
2023	A*	`conf`	A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning. NeurIPS Valeriia Cherepanova, Roman Levin, Gowthami Somepalli, Jonas Geiping, C. Bayan Bruss, Andrew Gordon Wilson, Tom Goldstein, Micah Goldblum
2023	J	`jnl`	A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning. CoRR Valeriia Cherepanova, Roman Levin, Gowthami Somepalli, Jonas Geiping, C. Bayan Bruss, Andrew Gordon Wilson, Tom Goldstein, Micah Goldblum
2023	—	`—`	Adversarial Robustness and Fairness in Deep Learning. Valeriia Cherepanova
2023	A*	`conf`	Transfer Learning with Deep Tabular Models. ICLR Roman Levin, Valeriia Cherepanova, Avi Schwarzschild, Arpit Bansal, C. Bayan Bruss, Tom Goldstein, Andrew Gordon Wilson, Micah Goldblum
2022	J	`jnl`	A Deep Dive into Dataset Imbalance and Bias in Face Identification. CoRR Valeriia Cherepanova, Steven Reich, Samuel Dooley, Hossein Souri, Micah Goldblum, Tom Goldstein
2022	J	`jnl`	Transfer Learning with Deep Tabular Models. CoRR Roman Levin, Valeriia Cherepanova, Avi Schwarzschild, Arpit Bansal, C. Bayan Bruss, Tom Goldstein, Andrew Gordon Wilson, Micah Goldblum
2021	J	`jnl`	Comparing Human and Machine Bias in Face Recognition. CoRR 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
2021	J	`jnl`	DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations. CoRR Eitan Borgnia, Jonas Geiping, Valeriia Cherepanova, Liam Fowl, Arjun Gupta, Amin Ghiasi, Furong Huang, Micah Goldblum, Tom Goldstein
2021	A*	`conf`	LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition. ICLR Valeriia Cherepanova, Micah Goldblum, Harrison Foley, Shiyuan Duan, John P. Dickerson, Gavin Taylor, Tom Goldstein
2021	J	`jnl`	LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition. CoRR Valeriia Cherepanova, Micah Goldblum, Harrison Foley, Shiyuan Duan, John P. Dickerson, Gavin Taylor, Tom Goldstein
2021	J	`jnl`	MetaBalance: High-Performance Neural Networks for Class-Imbalanced Data. CoRR Arpit Bansal, Micah Goldblum, Valeriia Cherepanova, Avi Schwarzschild, C. Bayan Bruss, Tom Goldstein
2021	Misc	`conf`	Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff. ICASSP Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Arjun Gupta
2021	J	`jnl`	Technical Challenges for Training Fair Neural Networks. CoRR Valeriia Cherepanova, Vedant Nanda, Micah Goldblum, John P. Dickerson, Tom Goldstein
2020	J	`jnl`	Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff. CoRR Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Arjun Gupta
2020	A*	`conf`	Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks. ICML Micah Goldblum, Steven Reich, Liam Fowl, Renkun Ni, Valeriia Cherepanova, Tom Goldstein
2020	J	`jnl`	Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks. CoRR Micah Goldblum, Steven Reich, Liam Fowl, Renkun Ni, Valeriia Cherepanova, Tom Goldstein