Publications by year
(#) denotes alphabetical order
On the Inductive Bias of Stacking Towards Improving Reasoning
Nikunj Saunshi, Stefani Karp, Shankar Krishnan, Sobhan Miryoosefi, Sashank Reddi, Sanjiv Kumar
To Appear at NeurIPS 2024
Landscape-Aware Growing: The Power of a Little LAG
Nikunj Saunshi*, Stefani Karp*, Sobhan Miryoosefi, Sashank Reddi, Sanjiv Kumar
Arxiv
Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning?
Khashayar Gatmiry, Nikunj Saunshi, Sashank Reddi, Stefanie Jegelka, Sanjiv Kumar
ICML 2024
Efficient Stagewise Pretraining via Progressive Subnetworks
Abhishek Panigrahi*, Nikunj Saunshi*, Kaifeng Lyu, Sobhan Miryoosefi, Sashank Reddi, Satyen Kale, Sanjiv Kumar
Arxiv
Task-Specific Skill Localization in Fine-tuned Language Models
Abhishek Panigrahi*, Nikunj Saunshi*, Haoyu Zhang, Sanjeev Arora
ICML 2023
Reasoning in Large Language Models Through Symbolic Math Word Problems
Vedant Gaur, Nikunj Saunshi
Findings of ACL 2023
[Talk]
Understanding Influence Functions and Datamodels via Harmonic Analysis
Nikunj Saunshi, Arushi Gupta, Mark Braverman, Sanjeev Arora
ICLR 2023
New Definitions and Evaluations for Saliency Methods: Staying Intrinsic, Complete and Sound
Arushi Gupta*, Nikunj Saunshi*, Dingli Yu*, Kaifeng Lyu, Sanjeev Arora
NeurIPS 2022 (Oral)
Understanding Contrastive Learning Requires Incorporating Inductive Biases
Nikunj Saunshi, Jordan Ash, Surbhi Goel, Dipendra Misra, Cyril Zhang, Sanjeev Arora, Sham Kakade, Akshay Krishnamurthy
ICML 2022
On Predicting Generalization using GANs
Yi Zhang, Arushi Gupta, Nikunj Saunshi, Sanjeev Arora
ICLR 2022 (Oral)
Predicting What You Already Know Helps: Provable Self-Supervised Learning
(#) Jason D. Lee, Qi Lei, Nikunj Saunshi, Jiacheng Zhuo
NeurIPS 2021
Nikunj Saunshi, Arushi Gupta, Wei Hu
ICML 2021
A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks
Nikunj Saunshi, Sadhika Malladi, Sanjeev Arora
ICLR 2021
[Talk]
A Sample Complexity Separation between Non-Convex and Convex Meta-Learning
Nikunj Saunshi, Yi Zhang, Mikhail Khodak, Sanjeev Arora
ICML 2020
[Talk]
Provable Representation Learning for Imitation Learning via Bi-level Optimization
(#) Sanjeev Arora, Simon S. Du, Sham Kakade, Yuping Luo, Nikunj Saunshi
ICML 2020
A Theoretical Analysis of Contrastive Unsupervised Representation Learning
(#) Sanjeev Arora, Hrishikesh Khandeparkar, Mikhail Khodak, Orestis Plevrakis, Nikunj Saunshi
ICML 2019
A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors
Mikhail Khodak*, Nikunj Saunshi*, Yingyu Liang, Tengyu Ma, Brandon Stewart and Sanjeev Arora
ACL 2018
A Compressed Sensing View of Unsupervised Text Embeddings, Bag-of-n-Grams, and LSTMs
(#) Sanjeev Arora, Mikhail Khodak, Nikunj Saunshi, Kiran Vodrahalli
ICLR 2018
[Blog]