Christina Baek

26 papers A* 11A 1Journal 14

Year	Rank	Type	Title / Venue / Authors
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
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	A*	`conf`	Context-Parametric Inversion: Why Instruction Finetuning May Not Actually Improve Context Reliance. ICLR Sachin Goyal, Christina Baek, J. Zico Kolter, Aditi Raghunathan
2025	A	`conf`	Theory of Agreement-on-the-Line in Linear Models and Gaussian Data. AISTATS Christina Baek, Aditi Raghunathan, J. Zico Kolter
2025	J	`jnl`	Weight Ensembling Improves Reasoning in Language Models. CoRR Xingyu Dang, Christina Baek, Kaiyue Wen, Zico Kolter, Aditi Raghunathan
2024	J	`jnl`	Context-Parametric Inversion: Why Instruction Finetuning May Not Actually Improve Context Reliance. CoRR Sachin Goyal, Christina Baek, J. Zico Kolter, Aditi Raghunathan
2024	A*	`conf`	On the Joint Interaction of Models, Data, and Features. ICLR Yiding Jiang, Christina Baek, J. Zico Kolter
2024	A*	`conf`	Predicting the Performance of Foundation Models via Agreement-on-the-Line. NeurIPS Rahul Saxena, Taeyoun Kim, Aman Mehra, Christina Baek, J. Zico Kolter, Aditi Raghunathan
2024	J	`jnl`	Predicting the Performance of Foundation Models via Agreement-on-the-Line. CoRR Aman Mehra, Rahul Saxena, Taeyoun Kim, Christina Baek, Zico Kolter, Aditi Raghunathan
2024	A*	`conf`	Test-Time Adaptation Induces Stronger Accuracy and Agreement-on-the-Line. NeurIPS Eungyeup Kim, Mingjie Sun, Christina Baek, Aditi Raghunathan, J. Zico Kolter
2024	A*	`conf`	Why is SAM Robust to Label Noise? ICLR Christina Baek, J. Zico Kolter, Aditi Raghunathan
2024	J	`jnl`	Why is SAM Robust to Label Noise? CoRR Christina Baek, Zico Kolter, Aditi Raghunathan
2023	J	`jnl`	On the Joint Interaction of Models, Data, and Features. CoRR Yiding Jiang, Christina Baek, J. Zico Kolter
2022	J	`jnl`	Agreement-on-the-Line: Predicting the Performance of Neural Networks under Distribution Shift. CoRR Christina Baek, Yiding Jiang, Aditi Raghunathan, Zico Kolter
2022	A*	`conf`	Agreement-on-the-line: Predicting the Performance of Neural Networks under Distribution Shift. NeurIPS Christina Baek, Yiding Jiang, Aditi Raghunathan, J. Zico Kolter
2022	A*	`conf`	Assessing Generalization of SGD via Disagreement. ICLR Yiding Jiang, Vaishnavh Nagarajan, Christina Baek, J. Zico Kolter
2022	J	`jnl`	Computational Benefits of Intermediate Rewards for Goal-Reaching Policy Learning. J. Artif. Intell. Res. Yuexiang Zhai, Christina Baek, Zhengyuan Zhou, Jiantao Jiao, Yi Ma
2022	A*	`conf`	Efficient Maximal Coding Rate Reduction by Variational Forms. CVPR Christina Baek, Ziyang Wu, Kwan Ho Ryan Chan, Tianjiao Ding, Yi Ma, Benjamin D. Haeffele
2022	J	`jnl`	Efficient Maximal Coding Rate Reduction by Variational Forms. CoRR Christina Baek, Ziyang Wu, Kwan Ho Ryan Chan, Tianjiao Ding, Yi Ma, Benjamin D. Haeffele
2021	J	`jnl`	Assessing Generalization of SGD via Disagreement. CoRR Yiding Jiang, Vaishnavh Nagarajan, Christina Baek, J. Zico Kolter
2021	J	`jnl`	Computational Benefits of Intermediate Rewards for Hierarchical Planning. CoRR Yuexiang Zhai, Christina Baek, Zhengyuan Zhou, Jiantao Jiao, Yi Ma
2021	A*	`conf`	Incremental Learning via Rate Reduction. CVPR Ziyang Wu, Christina Baek, Chong You, Yi Ma
2020	J	`jnl`	Incremental Learning via Rate Reduction. CoRR Ziyang Wu, Christina Baek, Chong You, Yi Ma
2018	A*	`conf`	Perception-Action-Learning System for Mobile Social-Service Robots Using Deep Learning. AAAI Beom-Jin Lee, Jinyoung Choi, Chung-Yeon Lee, Kyung-Wha Park, Sungjun Choi, Cheolho Han, Dong-Sig Han, Christina Baek, Patrick Mokodir Emaase, Byoung-Tak Zhang
2018	A*	`conf`	Robust Human Following by Deep Bayesian Trajectory Prediction for Home Service Robots. ICRA Beom-Jin Lee, Jinyoung Choi, Christina Baek, Byoung-Tak Zhang
2017	J	`jnl`	In vitro molecular machine learning algorithm via symmetric internal loops of DNA. Biosyst. Ji-Hoon Lee, Seung Hwan Lee, Christina Baek, Hyo-Sun Chun, Je-Hwan Ryu, Jin-Woo Kim, Russell J. Deaton, Byoung-Tak Zhang