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ORCIDSadhika Malladi
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2020 – today
- 2024
[c8]Runzhe Wang, Sadhika Malladi, Tianhao Wang, Kaifeng Lyu, Zhiyuan Li:
The Marginal Value of Momentum for Small Learning Rate SGD. ICLR 2024- [c7]Abhishek Panigrahi, Sadhika Malladi, Mengzhou Xia, Sanjeev Arora:
Trainable Transformer in Transformer. ICML 2024 - [c6]Mengzhou Xia, Sadhika Malladi, Suchin Gururangan, Sanjeev Arora, Danqi Chen:
LESS: Selecting Influential Data for Targeted Instruction Tuning. ICML 2024 - [i11]Mengzhou Xia, Sadhika Malladi, Suchin Gururangan, Sanjeev Arora, Danqi Chen:
LESS: Selecting Influential Data for Targeted Instruction Tuning. CoRR abs/2402.04333 (2024) - [i10]Angelica Chen, Sadhika Malladi, Lily H. Zhang, Xinyi Chen, Qiuyi Zhang, Rajesh Ranganath, Kyunghyun Cho:
Preference Learning Algorithms Do Not Learn Preference Rankings. CoRR abs/2405.19534 (2024) - [i9]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:
CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs. CoRR abs/2406.18521 (2024) - [i8]Weijia Shi, Jaechan Lee, Yangsibo Huang, Sadhika Malladi, Jieyu Zhao, Ari Holtzman, Daogao Liu, Luke Zettlemoyer, Noah A. Smith, Chiyuan Zhang:
MUSE: Machine Unlearning Six-Way Evaluation for Language Models. CoRR abs/2407.06460 (2024) - 2023
- [c5]Sadhika Malladi, Alexander Wettig, Dingli Yu, Danqi Chen, Sanjeev Arora:
A Kernel-Based View of Language Model Fine-Tuning. ICML 2023: 23610-23641 - [c4]Sadhika Malladi, Tianyu Gao, Eshaan Nichani, Alex Damian, Jason D. Lee, Danqi Chen, Sanjeev Arora:
Fine-Tuning Language Models with Just Forward Passes. NeurIPS 2023 - [i7]Sadhika Malladi, Tianyu Gao, Eshaan Nichani, Alex Damian, Jason D. Lee, Danqi Chen, Sanjeev Arora:
Fine-Tuning Language Models with Just Forward Passes. CoRR abs/2305.17333 (2023) - [i6]Abhishek Panigrahi, Sadhika Malladi, Mengzhou Xia, Sanjeev Arora:
Trainable Transformer in Transformer. CoRR abs/2307.01189 (2023) - [i5]Runzhe Wang, Sadhika Malladi, Tianhao Wang, Kaifeng Lyu, Zhiyuan Li
:
The Marginal Value of Momentum for Small Learning Rate SGD. CoRR abs/2307.15196 (2023) - 2022
- [c3]Sadhika Malladi, Kaifeng Lyu, Abhishek Panigrahi, Sanjeev Arora:
On the SDEs and Scaling Rules for Adaptive Gradient Algorithms. NeurIPS 2022 - [i4]Sadhika Malladi, Kaifeng Lyu, Abhishek Panigrahi, Sanjeev Arora:
On the SDEs and Scaling Rules for Adaptive Gradient Algorithms. CoRR abs/2205.10287 (2022) - [i3]Sadhika Malladi, Alexander Wettig, Dingli Yu, Danqi Chen, Sanjeev Arora:
A Kernel-Based View of Language Model Fine-Tuning. CoRR abs/2210.05643 (2022) - 2021
- [c2]Nikunj Saunshi, Sadhika Malladi, Sanjeev Arora:
A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks. ICLR 2021 - [c1]Zhiyuan Li, Sadhika Malladi, Sanjeev Arora:
On the Validity of Modeling SGD with Stochastic Differential Equations (SDEs). NeurIPS 2021: 12712-12725 - [i2]Zhiyuan Li, Sadhika Malladi, Sanjeev Arora:
On the Validity of Modeling SGD with Stochastic Differential Equations (SDEs). CoRR abs/2102.12470 (2021) - 2020
- [i1]Nikunj Saunshi, Sadhika Malladi, Sanjeev Arora:
A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks. CoRR abs/2010.03648 (2020)
2010 – 2019
- 2016
- [j1]Sheida Nabavi, Daniel Schmolze, Mayinuer Maitituoheti, Sadhika Malladi, Andrew H. Beck:
EMDomics: a robust and powerful method for the identification of genes differentially expressed between heterogeneous classes. Bioinform. 32(4): 533-541 (2016)
Coauthor Index
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