Abhishek Panigrahi

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Sanjeev AroraProfessor of Computer Science, Princeton UniversityVerified email at princeton.edu
Animesh MukherjeeProfessor of Computer Science, IIT Kharagpur, Distinguished Member, ACMVerified email at cse.iitkgp.ac.in
Sadhika MalladiPrinceton UniversityVerified email at princeton.edu
Navin GoyalMicrosoft ResearchVerified email at microsoft.com
Suman Kalyan MaityMassachusetts Institute of TechnologyVerified email at mit.edu
Haoyu ZhaoPrinceton UniversityVerified email at princeton.edu
Nikunj SaunshiResearch Scientist, GoogleVerified email at google.com
Kaifeng LyuSimons Institute, UC BerkeleyVerified email at princeton.edu
Zhiyuan LiAssistant Professor, Toyota Technological Institute at ChicagoVerified email at ttic.edu
Harsha Vardhan SimhadriMicrosoft ResearchVerified email at microsoft.com
Chiranjib BhattacharyyaProfessor, Indian Institute of ScienceVerified email at csa.iisc.ernet.in
Pawan GoyalAssociate Professor, Computer Science and Engineering, IIT KharagpurVerified email at cse.iitkgp.ac.in
Arundhati BanerjeeMachine Learning Department, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Praneeth NetrapalliGoogle ResearchVerified email at google.com
Raghav SomaniThe D. E. Shaw GroupVerified email at cs.washington.edu
Rong GeDuke UniversityVerified email at cs.duke.edu
Abhishek ShettyPostdoctoral Fellow, Massachussetts Institute of TechnologyVerified email at berkeley.edu
Sayan GhoshAmazon AWSVerified email at cs.unc.edu
C.-C. Jay KuoMing Hsieh Chair Professor in ECE-Systems, University of Southern CaliforniaVerified email at sipi.usc.edu
Mengzhou XiaPrinceton UniversityVerified email at princeton.edu

Abhishek Panigrahi

Graduate Student, Princeton University

Verified email at princeton.edu - Homepage

Machine Learning and Optimization Natural Language Processing


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Understanding gradient descent on the edge of stability in deep learning S Arora, Z Li, A Panigrahi International Conference on Machine Learning, 948-1024, 2022	124	2022
Word2Sense: Sparse interpretable word embeddings A Panigrahi, HV Simhadri, C Bhattacharyya Proceedings of the 57th annual meeting of the Association for Computational …, 2019	90	2019
Task-specific skill localization in fine-tuned language models A Panigrahi, N Saunshi, H Zhao, S Arora International Conference on Machine Learning, 27011-27033, 2023	78	2023
On the SDEs and scaling rules for adaptive gradient algorithms S Malladi, K Lyu, A Panigrahi, S Arora Advances in Neural Information Processing Systems 35, 7697-7711, 2022	51	2022
Non-Gaussianity of stochastic gradient noise A Panigrahi, R Somani, N Goyal, P Netrapalli arXiv preprint arXiv:1910.09626, 2019	50	2019
Do transformers parse while predicting the masked word? H Zhao, A Panigrahi, R Ge, S Arora arXiv preprint arXiv:2303.08117, 2023	45	2023
Effect of Activation Functions on the Training of Overparametrized Neural Nets A Panigrahi, A Shetty, N Goyal arXiv preprint arXiv:1908.05660, 2019	34	2019
DeepTagRec: A content-cum-user based tag recommendation framework for stack overflow SK Maity, A Panigrahi, S Ghosh, A Banerjee, P Goyal, A Mukherjee Advances in Information Retrieval: 41st European Conference on IR Research …, 2019	32	2019
Book reading behavior on goodreads can predict the amazon best sellers SK Maity, A Panigrahi, A Mukherjee Proceedings of the 2017 IEEE/ACM International Conference on Advances in …, 2017	28	2017
Analysis on gradient propagation in batch normalized residual networks A Panigrahi, Y Chen, CCJ Kuo arXiv preprint arXiv:1812.00342, 2018	23	2018
Trainable transformer in transformer A Panigrahi, S Malladi, M Xia, S Arora arXiv preprint arXiv:2307.01189, 2023	21	2023
Analyzing social book reading behavior on goodreads and how it predicts amazon best sellers SK Maity, A Panigrahi, A Mukherjee Influence and Behavior Analysis in Social Networks and Social Media, 211-235, 2019	16	2019
Efficient stagewise pretraining via progressive subnetworks A Panigrahi, N Saunshi, K Lyu, S Miryoosefi, S Reddi, S Kale, S Kumar arXiv preprint arXiv:2402.05913, 2024	7	2024
Learning and generalization in rnns A Panigrahi, N Goyal Advances in Neural Information Processing Systems 34, 21112-21124, 2021	3	2021
Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate Modality Imbalance in VLMs? S Park, A Panigrahi, Y Cheng, D Yu, A Goyal, S Arora arXiv preprint arXiv:2501.02669, 2025	1	2025
Progressive distillation induces an implicit curriculum A Panigrahi, B Liu, S Malladi, A Risteski, S Goel arXiv preprint arXiv:2410.05464, 2024	1*	2024
Representing rule-based chatbots with transformers D Friedman, A Panigrahi, D Chen arXiv preprint arXiv:2407.10949, 2024	1	2024
On the Power of Context-Enhanced Learning in LLMs X Zhu, A Panigrahi, S Arora arXiv preprint arXiv:2503.01821, 2025		2025
Algorithms for Codenames D Friedman, A Panigrahi		2021

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