John Kirchenbauer

33 papers A* 8A 1Journal 24

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Antidistillation Fingerprinting. CoRR Yixuan Even Xu, John Kirchenbauer, Yash Savani, Asher Trockman, Alexander Robey, Tom Goldstein, Fei Fang, J. Zico Kolter
2026	J	`jnl`	Multi-Token Prediction via Self-Distillation. CoRR John Kirchenbauer, Abhimanyu Hans, Brian R. Bartoldson, Micah Goldblum, Ashwinee Panda, Tom Goldstein
2025	J	`jnl`	A Fictional Q&A Dataset for Studying Memorization and Knowledge Acquisition. CoRR John Kirchenbauer, Janny Mongkolsupawan, Yuxin Wen, Tom Goldstein, Daphne Ippolito
2025	J	`jnl`	Democratizing AI: Open-source Scalable LLM Training on GPU-based Supercomputers. CoRR Siddharth Singh, Prajwal Singhania, Aditya K. Ranjan, John Kirchenbauer, Jonas Geiping, Yuxin Wen, Neel Jain, Abhimanyu Hans, Manli Shu, Aditya Tomar, Tom Goldstein, Abhinav Bhatele
2025	J	`jnl`	Exploiting Sparsity for Long Context Inference: Million Token Contexts on Commodity GPUs. CoRR Ryan Synk, Monte Hoover, John Kirchenbauer, Neel Jain, Alex Stein, Manli Shu, Josue Melendez Sanchez, Ramani Duraiswami, Tom Goldstein
2025	J	`jnl`	Gemstones: A Model Suite for Multi-Faceted Scaling Laws. CoRR Sean McLeish, John Kirchenbauer, David Yu Miller, Siddharth Singh, Abhinav Bhatele, Micah Goldblum, Ashwinee Panda, Tom Goldstein
2025	J	`jnl`	Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach. CoRR Jonas Geiping, Sean McLeish, Neel Jain, John Kirchenbauer, Siddharth Singh, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Tom Goldstein
2025	J	`jnl`	Teaching Pretrained Language Models to Think Deeper with Retrofitted Recurrence. CoRR Sean McLeish, Ang Li, John Kirchenbauer, Dayal Singh Kalra, Brian R. Bartoldson, Bhavya Kailkhura, Avi Schwarzschild, Jonas Geiping, Tom Goldstein, Micah Goldblum
2025	J	`jnl`	The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text. CoRR Nikhil Kandpal, Brian Lester, Colin Raffel, Sebastian Majstorovic, Stella Biderman, Baber Abbasi, Luca Soldaini, Enrico Shippole, A. Feder Cooper, Aviya Skowron, John Kirchenbauer, Shayne Longpre, Lintang Sutawika, Alon Albalak, Zhenlin Xu, Guilherme Penedo, Loubna Ben Allal, Elie Bakouch, John David Pressman, Honglu Fan, Dashiell Stander, Guangyu Song, Aaron Gokaslan, Tom Goldstein, Brian R. Bartoldson, Bhavya Kailkhura, Tyler Murray
2025	J	`jnl`	When Can You Get Away with Low Memory Adam? CoRR Dayal Singh Kalra, John Kirchenbauer, Maissam Barkeshli, Tom Goldstein
2025	J	`jnl`	Zero-Shot Vision Encoder Grafting via LLM Surrogates. CoRR Kaiyu Yue, Vasu Singla, Menglin Jia, John Kirchenbauer, Rifaa Qadri, Zikui Cai, Abhinav Bhatele, Furong Huang, Tom Goldstein
2024	A*	`conf`	Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs. NeurIPS Abhimanyu Hans, John Kirchenbauer, Yuxin Wen, Neel Jain, Hamid Kazemi, Prajwal Singhania, Siddharth Singh, Gowthami Somepalli, Jonas Geiping, Abhinav Bhatele, Tom Goldstein
2024	J	`jnl`	Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs. CoRR Abhimanyu Hans, Yuxin Wen, Neel Jain, John Kirchenbauer, Hamid Kazemi, Prajwal Singhania, Siddharth Singh, Gowthami Somepalli, Jonas Geiping, Abhinav Bhatele, Tom Goldstein
2024	A	`conf`	Democratizing AI: Open-source Scalable LLM Training on GPU-based Supercomputers. SC Siddharth Singh, Prajwal Singhania, Aditya K. Ranjan, John Kirchenbauer, Jonas Geiping, Yuxin Wen, Neel Jain, Abhimanyu Hans, Manli Shu, Aditya Tomar, Tom Goldstein, Abhinav Bhatele
2024	J	`jnl`	GenQA: Generating Millions of Instructions from a Handful of Prompts. CoRR Jiuhai Chen, Rifaa Qadri, Yuxin Wen, Neel Jain, John Kirchenbauer, Tianyi Zhou, Tom Goldstein
2024	J	`jnl`	LMD3: Language Model Data Density Dependence. CoRR John Kirchenbauer, Garrett Honke, Gowthami Somepalli, Jonas Geiping, Daphne Ippolito, Katherine Lee, Tom Goldstein, David Andre
2024	A*	`conf`	NEFTune: Noisy Embeddings Improve Instruction Finetuning. ICLR Neel Jain, Ping-Yeh Chiang, Yuxin Wen, John Kirchenbauer, Hong-Min Chu, Gowthami Somepalli, Brian R. Bartoldson, Bhavya Kailkhura, Avi Schwarzschild, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
2024	J	`jnl`	OPTune: Efficient Online Preference Tuning. CoRR Lichang Chen, Jiuhai Chen, Chenxi Liu, John Kirchenbauer, Davit Soselia, Chen Zhu, Tom Goldstein, Tianyi Zhou, Heng Huang
2024	A*	`conf`	On the Reliability of Watermarks for Large Language Models. ICLR John Kirchenbauer, Jonas Geiping, Yuxin Wen, Manli Shu, Khalid Saifullah, Kezhi Kong, Kasun Fernando, Aniruddha Saha, Micah Goldblum, Tom Goldstein
2024	A*	`conf`	Transformers Can Do Arithmetic with the Right Embeddings. NeurIPS Sean McLeish, Arpit Bansal, Alex Stein, Neel Jain, John Kirchenbauer, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Jonas Geiping, Avi Schwarzschild, Tom Goldstein
2024	J	`jnl`	Transformers Can Do Arithmetic with the Right Embeddings. CoRR Sean McLeish, Arpit Bansal, Alex Stein, Neel Jain, John Kirchenbauer, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Jonas Geiping, Avi Schwarzschild, Tom Goldstein
2023	A*	`conf`	A Watermark for Large Language Models. ICML John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, Tom Goldstein
2023	J	`jnl`	A Watermark for Large Language Models. CoRR John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, Tom Goldstein
2023	J	`jnl`	Baseline Defenses for Adversarial Attacks Against Aligned Language Models. CoRR Neel Jain, Avi Schwarzschild, Yuxin Wen, Gowthami Somepalli, John Kirchenbauer, Ping-Yeh Chiang, Micah Goldblum, Aniruddha Saha, Jonas Geiping, Tom Goldstein
2023	J	`jnl`	Bring Your Own Data! Self-Supervised Evaluation for Large Language Models. CoRR Neel Jain, Khalid Saifullah, Yuxin Wen, John Kirchenbauer, Manli Shu, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	A*	`conf`	GOAT: A Global Transformer on Large-scale Graphs. ICML Kezhi Kong, Jiuhai Chen, John Kirchenbauer, Renkun Ni, C. Bayan Bruss, Tom Goldstein
2023	A*	`conf`	Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery. NeurIPS Yuxin Wen, Neel Jain, John Kirchenbauer, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	J	`jnl`	Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery. CoRR Yuxin Wen, Neel Jain, John Kirchenbauer, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	J	`jnl`	NEFTune: Noisy Embeddings Improve Instruction Finetuning. CoRR Neel Jain, Ping-Yeh Chiang, Yuxin Wen, John Kirchenbauer, Hong-Min Chu, Gowthami Somepalli, Brian R. Bartoldson, Bhavya Kailkhura, Avi Schwarzschild, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	J	`jnl`	On the Reliability of Watermarks for Large Language Models. CoRR John Kirchenbauer, Jonas Geiping, Yuxin Wen, Manli Shu, Khalid Saifullah, Kezhi Kong, Kasun Fernando, Aniruddha Saha, Micah Goldblum, Tom Goldstein
2023	J	`jnl`	Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust. CoRR Yuxin Wen, John Kirchenbauer, Jonas Geiping, Tom Goldstein
2023	A*	`conf`	Tree-Rings Watermarks: Invisible Fingerprints for Diffusion Images. NeurIPS Yuxin Wen, John Kirchenbauer, Jonas Geiping, Tom Goldstein
2022	J	`jnl`	What is Your Metric Telling You? Evaluating Classifier Calibration under Context-Specific Definitions of Reliability. CoRR John Kirchenbauer, Jacob Oaks, Eric Heim