Vithursan Thangarasa

24 papers A* 1A 2B 1Journal 15Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons. CoRR 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
2025	J	`jnl`	DREAM: Drafting with Refined Target Features and Entropy-Adaptive Cross-Attention Fusion for Multimodal Speculative Decoding. CoRR Yunhai Hu, Tianhua Xia, Zining Liu, Rahul Raman, Xingyu Liu, Bo Bao, Eric Sather, Vithursan Thangarasa, Sai Qian Zhang
2025	—	`conf`	MASSV: Multimodal Adaptation and Self-Data Distillation for Speculative Decoding of Vision-Language Models. EMNLP (Findings) Mugilan Ganesan, Shane Segal, Ankur Aggarwal, Nish Sinnadurai, Sean Lie, Vithursan Thangarasa
2025	J	`jnl`	MASSV: Multimodal Adaptation and Self-Data Distillation for Speculative Decoding of Vision-Language Models. CoRR Mugilan Ganesan, Shane Segal, Ankur Aggarwal, Nish Sinnadurai, Sean Lie, Vithursan Thangarasa
2025	J	`jnl`	REAP the Experts: Why Pruning Prevails for One-Shot MoE compression. CoRR Mike Lasby, Ivan Lazarevich, Nish Sinnadurai, Sean Lie, Yani Ioannou, Vithursan Thangarasa
2025	J	`jnl`	SD CoRR Mike Lasby, Nish Sinnadurai, Valavan Manohararajah, Sean Lie, Vithursan Thangarasa
2025	—	`conf`	Self-Data Distillation for Recovering Quality in Pruned Large Language Models. MLSys Vithursan Thangarasa, Ganesh Venkatesh, Mike Lasby, Nish Sinnadurai, Sean Lie
2025	J	`jnl`	TapOut: A Bandit-Based Approach to Dynamic Speculative Decoding. CoRR Aditya Sridhar, Nish Sinnadurai, Sean Lie, Vithursan Thangarasa
2024	J	`jnl`	Introducing v0.5 of the AI Safety Benchmark from MLCommons. CoRR 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
2024	—	`conf`	MediSwift: Efficient Sparse Pre-trained Biomedical Language Models. ACL (Findings) Vithursan Thangarasa, Mahmoud Salem, Shreyas Saxena, Chen-Yu Leong, Joel Hestness, Sean Lie
2024	J	`jnl`	MediSwift: Efficient Sparse Pre-trained Biomedical Language Models. CoRR Vithursan Thangarasa, Mahmoud Salem, Shreyas Saxena, Kevin Leong, Joel Hestness, Sean Lie
2024	J	`jnl`	Self-Data Distillation for Recovering Quality in Pruned Large Language Models. CoRR Vithursan Thangarasa, Ganesh Venkatesh, Nish Sinnadurai, Sean Lie
2024	A*	`conf`	Sparse-IFT: Sparse Iso-FLOP Transformations for Maximizing Training Efficiency. ICML Vithursan Thangarasa, Shreyas Saxena, Abhay Gupta, Sean Lie
2023	—	`conf`	RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid Network. MLSys Vitaliy Chiley, Vithursan Thangarasa, Abhay Gupta, Anshul Samar, Joel Hestness, Dennis DeCoste
2023	A	`conf`	SPDF: Sparse Pre-training and Dense Fine-tuning for Large Language Models. UAI Vithursan Thangarasa, Abhay Gupta, William Marshall, Tianda Li, Kevin Leong, Dennis DeCoste, Sean Lie, Shreyas Saxena
2023	J	`jnl`	SPDF: Sparse Pre-training and Dense Fine-tuning for Large Language Models. CoRR Vithursan Thangarasa, Abhay Gupta, William Marshall, Tianda Li, Kevin Leong, Dennis DeCoste, Sean Lie, Shreyas Saxena
2023	J	`jnl`	Sparse Iso-FLOP Transformations for Maximizing Training Efficiency. CoRR Shreyas Saxena, Vithursan Thangarasa, Abhay Gupta, Sean Lie
2022	J	`jnl`	RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid Network. CoRR Vitaliy Chiley, Vithursan Thangarasa, Abhay Gupta, Anshul Samar, Joel Hestness, Dennis DeCoste
2021	J	`jnl`	Memory Efficient 3D U-Net with Reversible Mobile Inverted Bottlenecks for Brain Tumor Segmentation. CoRR Mihir Pendse, Vithursan Thangarasa, Vitaliy Chiley, Ryan Holmdahl, Joel Hestness, Dennis DeCoste
2020	B	`conf`	Enabling Continual Learning with Differentiable Hebbian Plasticity. IJCNN Vithursan Thangarasa, Thomas Miconi, Graham W. Taylor
2020	J	`jnl`	Enabling Continual Learning with Differentiable Hebbian Plasticity. CoRR Vithursan Thangarasa, Thomas Miconi, Graham W. Taylor
2020	—	`conf`	Memory Efficient 3D U-Net with Reversible Mobile Inverted Bottlenecks for Brain Tumor Segmentation. BrainLes@MICCAI (2) Mihir Pendse, Vithursan Thangarasa, Vitaliy Chiley, Ryan Holmdahl, Joel Hestness, Dennis DeCoste
2018	A	`conf`	Self-Paced Learning with Adaptive Deep Visual Embeddings. BMVC Vithursan Thangarasa, Graham W. Taylor
2018	J	`jnl`	Self-Paced Learning with Adaptive Deep Visual Embeddings. CoRR Vithursan Thangarasa, Graham W. Taylor