Vignesh Kothapalli

According to our database1, Vignesh Kothapalli authored at least 18 papers between 2018 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models.
CoRR, February, 2026

2025
Distilling the Essence: Efficient Reasoning Distillation via Sequence Truncation.
CoRR, December, 2025

To Think or Not to Think: The Hidden Cost of Meta-Training with Excessive CoT Examples.
CoRR, December, 2025

CoT-ICL Lab: A Petri Dish for Studying Chain-of-Thought Learning from In-Context Demonstrations.
CoRR, February, 2025

Efficient AI in Practice: Training and Deployment of Efficient LLMs for Industry Applications.
CoRR, February, 2025

360Brew: A Decoder-only Foundation Model for Personalized Ranking and Recommendation.
CoRR, January, 2025

Can Kernel Methods Explain How the Data Affects Neural Collapse?
Trans. Mach. Learn. Res., 2025

From Spikes to Heavy Tails: Unveiling the Spectral Evolution of Neural Networks.
Trans. Mach. Learn. Res., 2025

Scaling Down, Serving Fast: Compressing and Deploying Efficient LLMs for Recommendation Systems.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

CoT-ICL Lab: A Synthetic Framework for Studying Chain-of-Thought Learning from In-Context Demonstrations.
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.
CoRR, 2024

Crafting Heavy-Tails in Weight Matrix Spectrum without Gradient Noise.
CoRR, 2024

Kernel vs. Kernel: Exploring How the Data Structure Affects Neural Collapse.
CoRR, 2024

2023
Neural Collapse: A Review on Modelling Principles and Generalization.
Trans. Mach. Learn. Res., 2023

A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks.
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.
Proceedings of the International Conference on Machine Learning, 2023

2022
Neural Collapse: A Review on Modelling Principles and Generalization.
CoRR, 2022

2018
Edge detection using fractional derivatives and information sets.
J. Electronic Imaging, 2018


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