Vignesh Kothapalli

According to our database, Vignesh Kothapalli authored at least 14 papers between 2018 and 2025.

Collaborative distances:

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

2025

CoT-ICL Lab: A Petri Dish for Studying Chain-of-Thought Learning from In-Context Demonstrations.

Vignesh Kothapalli, Hamed Firooz, Maziar Sanjabi

CoRR, February, 2025

Efficient AI in Practice: Training and Deployment of Efficient LLMs for Industry Applications.

Kayhan Behdin, Yun Dai, Ata Fatahi Baarzi, Aman Gupta, Qingquan Song, Shao Tang, Hejian Sang, Gregory Dexter, Sirou Zhu, Siyu Zhu, Tejas Dharamsi, Maziar Sanjabi, Vignesh Kothapalli, Hamed Firooz, Zhoutong Fu, Yihan Cao, Pin-Lun Hsu, Fedor Borisyuk, Zhipeng Wang, Rahul Mazumder, Natesh Pillai, Luke Simon

CoRR, February, 2025

360Brew: A Decoder-only Foundation Model for Personalized Ranking and Recommendation.

Hamed Firooz, Maziar Sanjabi, Adrian Englhardt, Aman Gupta, Ben Levine, Dre Olgiati, Gungor Polatkan, Iuliia Melnychuk, Karthik Ramgopal, Kirill Talanine, Kutta Srinivasan, Luke Simon, Natesh Sivasubramoniapillai, Necip Fazil Ayan, Qingquan Song, Samira Sriram, Souvik Ghosh, Tao Song, Vignesh Kothapalli, Xiaoling Zhai, Ya Xu, Yu Wang, Yun Dai

CoRR, January, 2025

Can Kernel Methods Explain How the Data Affects Neural Collapse?

Vignesh Kothapalli, Tom Tirer

Trans. Mach. Learn. Res., 2025

From Spikes to Heavy Tails: Unveiling the Spectral Evolution of Neural Networks.

Vignesh Kothapalli, Tianyu Pang, Shenyang Deng, Zongmin Liu, Yaoqing Yang

Trans. Mach. Learn. Res., 2025

CoT-ICL Lab: A Synthetic Framework for Studying Chain-of-Thought Learning from In-Context Demonstrations.

Vignesh Kothapalli, Hamed Firooz, Maziar Sanjabi

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Liger Kernel: Efficient Triton Kernels for LLM Training.

Pin-Lun Hsu, Yun Dai, Vignesh Kothapalli, Qingquan Song, Shao Tang, Siyu Zhu, Steven Shimizu, Shivam Sahni, Haowen Ning, Yanning Chen

CoRR, 2024

Crafting Heavy-Tails in Weight Matrix Spectrum without Gradient Noise.

Vignesh Kothapalli, Tianyu Pang, Shenyang Deng, Zongmin Liu, Yaoqing Yang

CoRR, 2024

Kernel vs. Kernel: Exploring How the Data Structure Affects Neural Collapse.

Vignesh Kothapalli, Tom Tirer

CoRR, 2024

2023

Neural Collapse: A Review on Modelling Principles and Generalization.

Vignesh Kothapalli

Trans. Mach. Learn. Res., 2023

A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks.

Vignesh Kothapalli, Tom Tirer, Joan Bruna

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

Randomized Schur Complement Views for Graph Contrastive Learning.

Vignesh Kothapalli

Proceedings of the International Conference on Machine Learning, 2023

2022

Neural Collapse: A Review on Modelling Principles and Generalization.

Vignesh Kothapalli, Ebrahim Rasromani, Vasudev Awatramani

CoRR, 2022

2018

Edge detection using fractional derivatives and information sets.

Vignesh Kothapalli, Shaveta Arora, Madasu Hanmandlu

J. Electronic Imaging, 2018