Pratyush Maini

43 papers A* 14A 1Journal 26Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	DatBench: Discriminative, Faithful, and Efficient VLM Evaluations. CoRR Siddharth Joshi, Haoli Yin, Rishabh Adiga, Ricardo Monti, Aldo Carranza, Alex Fang, Alvin Deng, Amro Abbas, Brett W. Larsen, Cody Blakeney, Darren Teh, David Schwab, Fan Pan, Haakon Mongstad, Jack Urbanek, Jason Lee, Jason Telanoff, Josh Wills, Kaleigh Mentzer, Luke Merrick, Parth Doshi, Paul Burstein, Pratyush Maini, Scott Loftin, Spandan Das, Tony Jiang, Vineeth Dorna, Zhengping Wang, Bogdan Gaza, Ari Morcos, Matthew L. Leavitt
2026	J	`jnl`	The Finetuner's Fallacy: When to Pretrain with Your Finetuning Data. CoRR Christina Baek, Ricardo Pio Monti, David Schwab, Amro Abbas, Rishabh Adiga, Cody Blakeney, Maximilian Böther, Paul Burstein, Aldo Gael Carranza, Alvin Deng, Parth Doshi, Vineeth Dorna, Alex Fang, Tony Jiang, Siddharth Joshi, Brett W. Larsen, Jason Chan Lee, Katherine L. Mentzer, Luke Merrick, Haakon Mongstad, Fan Pan, Anshuman Suri, Darren Teh, Jason Telanoff, Jack Urbanek, Zhengping Wang, Josh Wills, Haoli Yin, Aditi Raghunathan, J. Zico Kolter, Bogdan Gaza, Ari Morcos, Matthew L. Leavitt, Pratyush Maini
2026	J	`jnl`	When Should We Introduce Safety Interventions During Pretraining? CoRR Dylan Sam, Sachin Goyal, Pratyush Maini, Alexander Robey, J. Zico Kolter
2026	J	`jnl`	ÜberWeb: Insights from Multilingual Curation for a 20-Trillion-Token Dataset. CoRR Aldo Gael Carranza, Kaleigh Mentzer, Ricardo Pio Monti, Alex Fang, Alvin Deng, Amro Abbas, Anshuman Suri, Brett W. Larsen, Cody Blakeney, Darren Teh, David Schwab, Diego Kiner, Fan Pan, Haakon Mongstad, Haoli Yin, Jack Urbanek, Jason Lee, Jason Telanoff, Josh Wills, Luke Merrick, Maximilian Böther, Parth Doshi, Paul Burstein, Pratyush Maini, Rishabh Adiga, Siddharth Joshi, Spandan Das, Tony Jiang, Vineeth Dorna, Zhengping Wang, Bogdan Gaza, Ari Morcos, Matthew L. Leavitt
2025	J	`jnl`	BeyondWeb: Lessons from Scaling Synthetic Data for Trillion-scale Pretraining. CoRR Pratyush Maini, Vineeth Dorna, Parth Doshi, Aldo Carranza, Fan Pan, Jack Urbanek, Paul Burstein, Alex Fang, Alvin Deng, Amro Abbas, Brett W. Larsen, Cody Blakeney, Charvi Bannur, Christina Baek, Darren Teh, David Schwab, Haakon Mongstad, Haoli Yin, Josh Wills, Kaleigh Mentzer, Luke Merrick, Ricardo Monti, Rishabh Adiga, Siddharth Joshi, Spandan Das, Zhengping Wang, Bogdan Gaza, Ari Morcos, Matthew L. Leavitt
2025	J	`jnl`	Luxical: High-Speed Lexical-Dense Text Embeddings. CoRR Luke Merrick, Alex Fang, Aldo Carranza, Alvin Deng, Amro Abbas, Brett W. Larsen, Cody Blakeney, Darren Teh, David Schwab, Fan Pan, Haakon Mongstad, Haoli Yin, Jack Urbanek, Jason Lee, Jason Telanoff, Josh Wills, Kaleigh Mentzer, Paul Burstein, Parth Doshi, Paul Burnstein, Pratyush Maini, Ricardo Monti, Rishabh Adiga, Scott Loftin, Siddharth Joshi, Spandan Das, Tony Jiang, Vineeth Dorna, Zhengping Wang, Bogdan Gaza, Ari Morcos, Matthew L. Leavitt
2025	A*	`conf`	Memorization Sinks: Isolating Memorization during LLM Training. ICML Gaurav Rohit Ghosal, Pratyush Maini, Aditi Raghunathan
2025	J	`jnl`	Memorization Sinks: Isolating Memorization during LLM Training. CoRR Gaurav R. Ghosal, Pratyush Maini, Aditi Raghunathan
2025	J	`jnl`	OpenUnlearning: Accelerating LLM Unlearning via Unified Benchmarking of Methods and Metrics. CoRR Vineeth Dorna, Anmol Mekala, Wenlong Zhao, Andrew McCallum, Zachary C. Lipton, J. Zico Kolter, Pratyush Maini
2025	J	`jnl`	Peeking Behind Closed Doors: Risks of LLM Evaluation by Private Data Curators. CoRR Hritik Bansal, Pratyush Maini
2025	A*	`conf`	STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings. ICML Saksham Rastogi, Pratyush Maini, Danish Pruthi
2025	J	`jnl`	STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings. CoRR Saksham Rastogi, Pratyush Maini, Danish Pruthi
2025	J	`jnl`	Safety Pretraining: Toward the Next Generation of Safe AI. CoRR Pratyush Maini, Sachin Goyal, Dylan Sam, Alexander Robey, Yash Savani, Yiding Jiang, Andy Zou, Zacharcy C. Lipton, J. Zico Kolter
2025	A*	`conf`	Unlocking Post-hoc Dataset Inference with Synthetic Data. ICML Bihe Zhao, Pratyush Maini, Franziska Boenisch, Adam Dziedzic
2025	J	`jnl`	Unlocking Post-hoc Dataset Inference with Synthetic Data. CoRR Bihe Zhao, Pratyush Maini, Franziska Boenisch, Adam Dziedzic
2024	A*	`conf`	LLM Dataset Inference: Did you train on my dataset? NeurIPS Pratyush Maini, Hengrui Jia, Nicolas Papernot, Adam Dziedzic
2024	J	`jnl`	LLM Dataset Inference: Did you train on my dataset? CoRR Pratyush Maini, Hengrui Jia, Nicolas Papernot, Adam Dziedzic
2024	—	`conf`	Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling. ACL (1) Pratyush Maini, Skyler Seto, Richard He Bai, David Grangier, Yizhe Zhang, Navdeep Jaitly
2024	J	`jnl`	Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling. CoRR Pratyush Maini, Skyler Seto, He Bai, David Grangier, Yizhe Zhang, Navdeep Jaitly
2024	A*	`conf`	Rethinking LLM Memorization through the Lens of Adversarial Compression. NeurIPS Avi Schwarzschild, Zhili Feng, Pratyush Maini, Zachary C. Lipton, J. Zico Kolter
2024	J	`jnl`	Rethinking LLM Memorization through the Lens of Adversarial Compression. CoRR Avi Schwarzschild, Zhili Feng, Pratyush Maini, Zachary C. Lipton, J. Zico Kolter
2024	A*	`conf`	Scaling Laws for Data Filtering - Data Curation Cannot be Compute Agnostic. CVPR Sachin Goyal, Pratyush Maini, Zachary C. Lipton, Aditi Raghunathan, J. Zico Kolter
2024	J	`jnl`	Scaling Laws for Data Filtering - Data Curation cannot be Compute Agnostic. CoRR Sachin Goyal, Pratyush Maini, Zachary C. Lipton, Aditi Raghunathan, J. Zico Kolter
2024	A*	`conf`	T-MARS: Improving Visual Representations by Circumventing Text Feature Learning. ICLR Pratyush Maini, Sachin Goyal, Zachary Chase Lipton, J. Zico Kolter, Aditi Raghunathan
2024	J	`jnl`	TOFU: A Task of Fictitious Unlearning for LLMs. CoRR Pratyush Maini, Zhili Feng, Avi Schwarzschild, Zachary C. Lipton, J. Zico Kolter
2024	A*	`conf`	Understanding Hallucinations in Diffusion Models through Mode Interpolation. NeurIPS Sumukh K. Aithal, Pratyush Maini, Zachary C. Lipton, J. Zico Kolter
2024	J	`jnl`	Understanding Hallucinations in Diffusion Models through Mode Interpolation. CoRR Sumukh K. Aithal, Pratyush Maini, Zachary C. Lipton, J. Zico Kolter
2023	A*	`conf`	Can Neural Network Memorization Be Localized? ICML Pratyush Maini, Michael Curtis Mozer, Hanie Sedghi, Zachary Chase Lipton, J. Zico Kolter, Chiyuan Zhang
2023	J	`jnl`	Can Neural Network Memorization Be Localized? CoRR Pratyush Maini, Michael C. Mozer, Hanie Sedghi, Zachary C. Lipton, J. Zico Kolter, Chiyuan Zhang
2023	A*	`conf`	Model-tuning Via Prompts Makes NLP Models Adversarially Robust. EMNLP Mrigank Raman, Pratyush Maini, J. Zico Kolter, Zachary C. Lipton, Danish Pruthi
2023	J	`jnl`	Model-tuning Via Prompts Makes NLP Models Adversarially Robust. CoRR Mrigank Raman, Pratyush Maini, J. Zico Kolter, Zachary C. Lipton, Danish Pruthi
2023	J	`jnl`	T-MARS: Improving Visual Representations by Circumventing Text Feature Learning. CoRR Pratyush Maini, Sachin Goyal, Zachary C. Lipton, J. Zico Kolter, Aditi Raghunathan
2022	A*	`conf`	Characterizing Datapoints via Second-Split Forgetting. NeurIPS Pratyush Maini, Saurabh Garg, Zachary C. Lipton, J. Zico Kolter
2022	J	`jnl`	Characterizing Datapoints via Second-Split Forgetting. CoRR Pratyush Maini, Saurabh Garg, Zachary C. Lipton, J. Zico Kolter
2022	A	`conf`	Perturbation type categorization for multiple adversarial perturbation robustness. UAI Pratyush Maini, Xinyun Chen, Bo Li, Dawn Song
2021	A*	`conf`	Data-Free Model Extraction. CVPR Jean-Baptiste Truong, Pratyush Maini, Robert J. Walls, Nicolas Papernot
2021	A*	`conf`	Dataset Inference: Ownership Resolution in Machine Learning. ICLR Pratyush Maini, Mohammad Yaghini, Nicolas Papernot
2021	J	`jnl`	Dataset Inference: Ownership Resolution in Machine Learning. CoRR Pratyush Maini, Mohammad Yaghini, Nicolas Papernot
2020	A*	`conf`	Adversarial Robustness Against the Union of Multiple Perturbation Models. ICML Pratyush Maini, Eric Wong, J. Zico Kolter
2020	J	`jnl`	Data-Free Model Extraction. CoRR Jean-Baptiste Truong, Pratyush Maini, Robert J. Walls, Nicolas Papernot
2020	—	`conf`	Why and when should you pool? Analyzing Pooling in Recurrent Architectures. EMNLP (Findings) Pratyush Maini, Keshav Kolluru, Danish Pruthi, Mausam
2020	J	`jnl`	Why and when should you pool? Analyzing Pooling in Recurrent Architectures. CoRR Pratyush Maini, Keshav Kolluru, Danish Pruthi, Mausam
2019	J	`jnl`	Adversarial Robustness Against the Union of Multiple Perturbation Models. CoRR Pratyush Maini, Eric Wong, J. Zico Kolter