Christina Baek

According to our database, Christina Baek authored at least 18 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

The Finetuner's Fallacy: When to Pretrain with Your Finetuning Data.

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

CoRR, March, 2026

2025

BeyondWeb: Lessons from Scaling Synthetic Data for Trillion-scale Pretraining.

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

CoRR, August, 2025

Weight Ensembling Improves Reasoning in Language Models.

Xingyu Dang, Christina Baek, Kaiyue Wen, Zico Kolter, Aditi Raghunathan

CoRR, April, 2025

Context-Parametric Inversion: Why Instruction Finetuning May Not Actually Improve Context Reliance.

Sachin Goyal, Christina Baek, J. Zico Kolter, Aditi Raghunathan

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Theory of Agreement-on-the-Line in Linear Models and Gaussian Data.

Christina Baek, Aditi Raghunathan, J. Zico Kolter

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Predicting the Performance of Foundation Models via Agreement-on-the-Line.

Rahul Saxena, Taeyoun Kim, Aman Mehra, Christina Baek, J. Zico Kolter, Aditi Raghunathan

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Test-Time Adaptation Induces Stronger Accuracy and Agreement-on-the-Line.

Eungyeup Kim, Mingjie Sun, Christina Baek, Aditi Raghunathan, J. Zico Kolter

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

On the Joint Interaction of Models, Data, and Features.

Yiding Jiang, Christina Baek, J. Zico Kolter

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Why is SAM Robust to Label Noise?

Christina Baek, J. Zico Kolter, Aditi Raghunathan

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2022

Computational Benefits of Intermediate Rewards for Goal-Reaching Policy Learning.

Yuexiang Zhai, Christina Baek, Zhengyuan Zhou, Jiantao Jiao, Yi Ma

J. Artif. Intell. Res., 2022

Agreement-on-the-line: Predicting the Performance of Neural Networks under Distribution Shift.

Christina Baek, Yiding Jiang, Aditi Raghunathan, J. Zico Kolter

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Assessing Generalization of SGD via Disagreement.

Yiding Jiang, Vaishnavh Nagarajan, Christina Baek, J. Zico Kolter

Proceedings of the Tenth International Conference on Learning Representations, 2022

Efficient Maximal Coding Rate Reduction by Variational Forms.

Christina Baek, Ziyang Wu, Kwan Ho Ryan Chan, Tianjiao Ding, Yi Ma, Benjamin D. Haeffele

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Computational Benefits of Intermediate Rewards for Hierarchical Planning.

Yuexiang Zhai, Christina Baek, Zhengyuan Zhou, Jiantao Jiao, Yi Ma

CoRR, 2021

Incremental Learning via Rate Reduction.

Ziyang Wu, Christina Baek, Chong You, Yi Ma

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2018

Robust Human Following by Deep Bayesian Trajectory Prediction for Home Service Robots.

Beom-Jin Lee, Jinyoung Choi, Christina Baek, Byoung-Tak Zhang

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Perception-Action-Learning System for Mobile Social-Service Robots Using Deep Learning.

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

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

In vitro molecular machine learning algorithm via symmetric internal loops of DNA.

Ji-Hoon Lee, Seung Hwan Lee, Christina Baek, Hyo-Sun Chun, Je-Hwan Ryu, Jin-Woo Kim, Russell J. Deaton, Byoung-Tak Zhang

Biosyst., 2017