Sadhika Malladi

According to our database, Sadhika Malladi authored at least 16 papers between 2016 and 2024.

Collaborative distances:

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

2024

Provable unlearning in topic modeling and downstream tasks.

Stanley Wei, Sadhika Malladi, Sanjeev Arora, Amartya Sanyal

CoRR, 2024

Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws.

Yiding Jiang, Allan Zhou, Zhili Feng, Sadhika Malladi, J. Zico Kolter

CoRR, 2024

Unintentional Unalignment: Likelihood Displacement in Direct Preference Optimization.

Noam Razin, Sadhika Malladi, Adithya Bhaskar, Danqi Chen, Sanjeev Arora, Boris Hanin

CoRR, 2024

Progressive distillation induces an implicit curriculum.

Abhishek Panigrahi, Bingbin Liu, Sadhika Malladi, Andrej Risteski, Surbhi Goel

CoRR, 2024

MUSE: Machine Unlearning Six-Way Evaluation for Language Models.

Weijia Shi, Jaechan Lee, Yangsibo Huang, Sadhika Malladi, Jieyu Zhao, Ari Holtzman, Daogao Liu, Luke Zettlemoyer, Noah A. Smith, Chiyuan Zhang

CoRR, 2024

CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs.

Zirui Wang, Mengzhou Xia, Luxi He, Howard Chen, Yitao Liu, Richard Zhu, Kaiqu Liang, Xindi Wu, Haotian Liu, Sadhika Malladi, Alexis Chevalier, Sanjeev Arora, Danqi Chen

CoRR, 2024

Preference Learning Algorithms Do Not Learn Preference Rankings.

Angelica Chen, Sadhika Malladi, Lily H. Zhang, Xinyi Chen, Qiuyi Zhang, Rajesh Ranganath, Kyunghyun Cho

CoRR, 2024

LESS: Selecting Influential Data for Targeted Instruction Tuning.

Mengzhou Xia, Sadhika Malladi, Suchin Gururangan, Sanjeev Arora, Danqi Chen

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Trainable Transformer in Transformer.

Abhishek Panigrahi, Sadhika Malladi, Mengzhou Xia, Sanjeev Arora

Proceedings of the Forty-first International Conference on Machine Learning, 2024

The Marginal Value of Momentum for Small Learning Rate SGD.

Runzhe Wang, Sadhika Malladi, Tianhao Wang, Kaifeng Lyu, Zhiyuan Li

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Fine-Tuning Language Models with Just Forward Passes.

Sadhika Malladi, Tianyu Gao, Eshaan Nichani, Alex Damian, Jason D. Lee, Danqi Chen, Sanjeev Arora

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Kernel-Based View of Language Model Fine-Tuning.

Sadhika Malladi, Alexander Wettig, Dingli Yu, Danqi Chen, Sanjeev Arora

Proceedings of the International Conference on Machine Learning, 2023

2022

On the SDEs and Scaling Rules for Adaptive Gradient Algorithms.

Sadhika Malladi, Kaifeng Lyu, Abhishek Panigrahi, Sanjeev Arora

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

2021

On the Validity of Modeling SGD with Stochastic Differential Equations (SDEs).

Zhiyuan Li, Sadhika Malladi, Sanjeev Arora

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks.

Nikunj Saunshi, Sadhika Malladi, Sanjeev Arora

Proceedings of the 9th International Conference on Learning Representations, 2021

2016

EMDomics: a robust and powerful method for the identification of genes differentially expressed between heterogeneous classes.

Sheida Nabavi, Daniel Schmolze, Mayinuer Maitituoheti, Sadhika Malladi, Andrew H. Beck

Bioinform., 2016