Vithursan Thangarasa

According to our database, Vithursan Thangarasa authored at least 21 papers between 2018 and 2026.

Collaborative distances:

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

2026

DREAM-R: Multimodal Speculative Reasoning with RL-Based Refined Drafting, Precise Verification, and Fully Parallel Execution.

Yunhai Hu, Zining Liu, Xiangyang Yin, Tianhua Xia, Bo Bao, Eric Sather, Vithursan Thangarasa, Sai Qian Zhang

CoRR, May, 2026

CodeQuant: Unified Clustering and Quantization for Enhanced Outlier Smoothing in Low-Precision Mixture-of-Experts.

Xiangyang Yin, Xingyu Liu, Tianhua Xia, Bo Bao, Vithursan Thangarasa, Valavan Manohararajah, Eric Sather, Sai Qian Zhang

CoRR, April, 2026

DREAM-S: Speculative Decoding with Searchable Drafting and Target-Aware Refinement for Multimodal Generation.

Zining Liu, Yunhai Hu, Tianhua Xia, B. O. Bao, Eric Sather, Vithursan Thangarasa, Sai Qian Zhang

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025

TapOut: A Bandit-Based Approach to Dynamic Speculative Decoding.

Aditya Sridhar, Nish Sinnadurai, Sean Lie, Vithursan Thangarasa

CoRR, November, 2025

REAP the Experts: Why Pruning Prevails for One-Shot MoE compression.

Mike Lasby, Ivan Lazarevich, Nish Sinnadurai, Sean Lie, Yani Ioannou, Vithursan Thangarasa

CoRR, October, 2025

SD²: Self-Distilled Sparse Drafters.

Mike Lasby, Nish Sinnadurai, Valavan Manohararajah, Sean Lie, Vithursan Thangarasa

CoRR, April, 2025

AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons.

Shaona Ghosh, Heather Frase, Adina Williams, Sarah Luger, Paul Röttger, Fazl Barez, Sean McGregor, Kenneth Fricklas, Mala Kumar, Quentin Feuillade-Montixi, Kurt D. Bollacker, Felix Friedrich, Ryan Tsang, Bertie Vidgen, Alicia Parrish, Chris Knotz, Eleonora Presani, Jonathan Bennion, Marisa Ferrara Boston, Mike Kuniavsky, Wiebke Hutiri, James Ezick, Malek Ben Salem, Rajat Sahay, Sujata S. Goswami, Usman Gohar, Ben Huang, Supheakmungkol Sarin, Elie Alhajjar, Canyu Chen, Roman Eng, Kashyap Ramanandula Manjusha, Virendra Mehta, Eileen Long, Murali Emani, Natan Vidra, Benjamin Rukundo, Abolfazl Shahbazi, Kongtao Chen, Rajat Ghosh, Vithursan Thangarasa, Pierre Peigné, Abhinav Singh, Max Bartolo, Satyapriya Krishna, Mubashara Akhtar, Rafael Gold, Cody Coleman, Luis Oala, Vassil Tashev, Joseph Marvin Imperial, Amy Russ, Sasidhar Kunapuli, Nicolas Miailhe, Julien Delaunay, Bhaktipriya Radharapu, Rajat Shinde, Tuesday, Debojyoti Dutta, Declan Grabb, Ananya Gangavarapu, Saurav Sahay, Agasthya Gangavarapu, Patrick Schramowski, Stephen Singam, Tom David, Xudong Han, Priyanka Mary Mammen, Tarunima Prabhakar, Venelin Kovatchev, Ahmed Ahmed, Kelvin N. Manyeki, Sandeep Madireddy, Foutse Khomh, Fedor Zhdanov, Joachim Baumann, Nina Vasan, Xianjun Yang, Carlos Mougn, Jibin Rajan Varghese, Hussain Chinoy, Seshakrishna Jitendar, Manil Maskey, Claire V. Hardgrove, Tianhao Li, Aakash Gupta, Emil Joswin, Yifan Mai, Shachi H. Kumar, Cigdem Patlak, Kevin Lu, Vincent Alessi, Sree Bhargavi Balija, Chenhe Gu, Robert Sullivan, James Gealy, Matt Lavrisa, James Goel, Peter Mattson, Percy Liang, Joaquin Vanschoren

CoRR, March, 2025

DREAM: Drafting with Refined Target Features and Entropy-Adaptive Cross-Attention Fusion for Multimodal Speculative Decoding.

Yunhai Hu, Tianhua Xia, Zining Liu, Rahul Raman, Xingyu Liu, Bo Bao, Eric Sather, Vithursan Thangarasa, Sai Qian Zhang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Self-Data Distillation for Recovering Quality in Pruned Large Language Models.

Vithursan Thangarasa, Ganesh Venkatesh, Mike Lasby, Nish Sinnadurai, Sean Lie

Proceedings of the Eighth Conference on Machine Learning and Systems, 2025

MASSV: Multimodal Adaptation and Self-Data Distillation for Speculative Decoding of Vision-Language Models.

Mugilan Ganesan, Shane Segal, Ankur Aggarwal, Nish Sinnadurai, Sean Lie, Vithursan Thangarasa

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

2024

Self-Data Distillation for Recovering Quality in Pruned Large Language Models.

Vithursan Thangarasa, Ganesh Venkatesh, Nish Sinnadurai, Sean Lie

CoRR, 2024

Introducing v0.5 of the AI Safety Benchmark from MLCommons.

Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, Victor Akinwande, Namir Al-Nuaimi, Najla Alfaraj, Elie Alhajjar, Lora Aroyo, Trupti Bavalatti, Borhane Blili-Hamelin, Kurt Bollacker, Rishi Bomassani, Marisa Ferrara Boston, Siméon Campos, Kal Chakra, Canyu Chen, Cody Coleman, Zacharie Delpierre Coudert, Leon Derczynski, Debojyoti Dutta, Ian Eisenberg, James Ezick, Heather Frase, Brian Fuller, Ram Gandikota, Agasthya Gangavarapu, Ananya Gangavarapu, James Gealy, Rajat Ghosh, James Goel, Usman Gohar, Subhra S. Goswami, Scott A. Hale, Wiebke Hutiri, Joseph Marvin Imperial, Surgan Jandial, Nick Judd, Felix Juefei-Xu, Foutse Khomh, Bhavya Kailkhura, Hannah Rose Kirk, Kevin Klyman, Chris Knotz, Michael Kuchnik, Shachi H. Kumar, Chris Lengerich, Bo Li, Zeyi Liao, Eileen Peters Long, Victor Lu, Yifan Mai, Priyanka Mary Mammen, Kelvin N. Manyeki, Sean McGregor, Virendra Mehta, Shafee Mohammed, Emanuel Moss, Lama Nachman, Dinesh Jinenhally Naganna, Amin Nikanjam, Besmira Nushi, Luis Oala, Iftach Orr, Alicia Parrish, Cigdem Patlak, William Pietri, Forough Poursabzi-Sangdeh, Eleonora Presani, Fabrizio Puletti, Paul Röttger, Saurav Sahay, Tim Santos, Nino Scherrer, Alice Schoenauer Sebag, Patrick Schramowski, Abolfazl Shahbazi, Vin Sharma, Xudong Shen, Vamsi Sistla, Leonard Tang, Davide Testuggine, Vithursan Thangarasa, Elizabeth Anne Watkins, Rebecca Weiss, Chris Welty, Tyler Wilbers, Adina Williams, Carole-Jean Wu, Poonam Yadav, Xianjun Yang, Yi Zeng, Wenhui Zhang, Fedor Zhdanov, Jiacheng Zhu, Percy Liang, Peter Mattson, Joaquin Vanschoren

CoRR, 2024

MediSwift: Efficient Sparse Pre-trained Biomedical Language Models.

Vithursan Thangarasa, Mahmoud Salem, Shreyas Saxena, Kevin Leong, Joel Hestness, Sean Lie

CoRR, 2024

Sparse-IFT: Sparse Iso-FLOP Transformations for Maximizing Training Efficiency.

Vithursan Thangarasa, Shreyas Saxena, Abhay Gupta, Sean Lie

Proceedings of the Forty-first International Conference on Machine Learning, 2024

MediSwift: Efficient Sparse Pre-trained Biomedical Language Models.

Vithursan Thangarasa, Mahmoud Salem, Shreyas Saxena, Chen-Yu Leong, Joel Hestness, Sean Lie

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Sparse Iso-FLOP Transformations for Maximizing Training Efficiency.

Shreyas Saxena, Vithursan Thangarasa, Abhay Gupta, Sean Lie

CoRR, 2023

SPDF: Sparse Pre-training and Dense Fine-tuning for Large Language Models.

Vithursan Thangarasa, Abhay Gupta, William Marshall, Tianda Li, Kevin Leong, Dennis DeCoste, Sean Lie, Shreyas Saxena

Proceedings of the Uncertainty in Artificial Intelligence, 2023

RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid Network.

Vitaliy Chiley, Vithursan Thangarasa, Abhay Gupta, Anshul Samar, Joel Hestness, Dennis DeCoste

Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

2020

Enabling Continual Learning with Differentiable Hebbian Plasticity.

Vithursan Thangarasa, Thomas Miconi, Graham W. Taylor

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Memory Efficient 3D U-Net with Reversible Mobile Inverted Bottlenecks for Brain Tumor Segmentation.

Mihir Pendse, Vithursan Thangarasa, Vitaliy Chiley, Ryan Holmdahl, Joel Hestness, Dennis DeCoste

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020

2018

Self-Paced Learning with Adaptive Deep Visual Embeddings.

Vithursan Thangarasa, Graham W. Taylor

Proceedings of the British Machine Vision Conference 2018, 2018