Vineeth Dorna

According to our database, Vineeth Dorna authored at least 10 papers between 2022 and 2026.

Collaborative distances:

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

2026

The Finetuner's Fallacy: When to Pretrain with Your Finetuning Data.

Christina Baek, Ricardo Pio Monti, David Schwab, Amro Abbas, Rishabh Adiga, Cody Blakeney, Maximilian Böther, Paul Burstein, Aldo Gael Carranza, Alvin Deng, Parth Doshi, Vineeth Dorna, Alex Fang, Tony Jiang, Siddharth Joshi, Brett W. Larsen, Jason Chan Lee, Katherine L. Mentzer, Luke Merrick, Haakon Mongstad, Fan Pan, Anshuman Suri, Darren Teh, Jason Telanoff, Jack Urbanek, Zhengping Wang, Josh Wills, Haoli Yin, Aditi Raghunathan, J. Zico Kolter, Bogdan Gaza, Ari Morcos, Matthew L. Leavitt, Pratyush Maini

CoRR, March, 2026

ÜberWeb: Insights from Multilingual Curation for a 20-Trillion-Token Dataset.

Aldo Gael Carranza, Kaleigh Mentzer, Ricardo Pio Monti, Alex Fang, Alvin Deng, Amro Abbas, Anshuman Suri, Brett W. Larsen, Cody Blakeney, Darren Teh, David Schwab, Diego Kiner, Fan Pan, Haakon Mongstad, Haoli Yin, Jack Urbanek, Jason Lee, Jason Telanoff, Josh Wills, Luke Merrick, Maximilian Böther, Parth Doshi, Paul Burstein, Pratyush Maini, Rishabh Adiga, Siddharth Joshi, Spandan Das, Tony Jiang, Vineeth Dorna, Zhengping Wang, Bogdan Gaza, Ari Morcos, Matthew L. Leavitt

CoRR, February, 2026

DatBench: Discriminative, Faithful, and Efficient VLM Evaluations.

Siddharth Joshi, Haoli Yin, Rishabh Adiga, Ricardo Monti, Aldo Carranza, Alex Fang, Alvin Deng, Amro Abbas, Brett W. Larsen, Cody Blakeney, Darren Teh, David Schwab, Fan Pan, Haakon Mongstad, Jack Urbanek, Jason Lee, Jason Telanoff, Josh Wills, Kaleigh Mentzer, Luke Merrick, Parth Doshi, Paul Burstein, Pratyush Maini, Scott Loftin, Spandan Das, Tony Jiang, Vineeth Dorna, Zhengping Wang, Bogdan Gaza, Ari Morcos, Matthew L. Leavitt

CoRR, January, 2026

2025

Luxical: High-Speed Lexical-Dense Text Embeddings.

Luke Merrick, Alex Fang, Aldo Carranza, Alvin Deng, Amro Abbas, Brett W. Larsen, Cody Blakeney, Darren Teh, David Schwab, Fan Pan, Haakon Mongstad, Haoli Yin, Jack Urbanek, Jason Lee, Jason Telanoff, Josh Wills, Kaleigh Mentzer, Paul Burstein, Parth Doshi, Paul Burnstein, Pratyush Maini, Ricardo Monti, Rishabh Adiga, Scott Loftin, Siddharth Joshi, Spandan Das, Tony Jiang, Vineeth Dorna, Zhengping Wang, Bogdan Gaza, Ari Morcos, Matthew L. Leavitt

CoRR, December, 2025

BeyondWeb: Lessons from Scaling Synthetic Data for Trillion-scale Pretraining.

Pratyush Maini, Vineeth Dorna, Parth Doshi, Aldo Carranza, Fan Pan, Jack Urbanek, Paul Burstein, Alex Fang, Alvin Deng, Amro Abbas, Brett W. Larsen, Cody Blakeney, Charvi Bannur, Christina Baek, Darren Teh, David Schwab, Haakon Mongstad, Haoli Yin, Josh Wills, Kaleigh Mentzer, Luke Merrick, Ricardo Monti, Rishabh Adiga, Siddharth Joshi, Spandan Das, Zhengping Wang, Bogdan Gaza, Ari Morcos, Matthew L. Leavitt

CoRR, August, 2025

OpenUnlearning: Accelerating LLM Unlearning via Unified Benchmarking of Methods and Metrics.

Vineeth Dorna, Anmol Mekala, Wenlong Zhao, Andrew McCallum, Zachary C. Lipton, J. Zico Kolter, Pratyush Maini

CoRR, June, 2025

Alternate Preference Optimization for Unlearning Factual Knowledge in Large Language Models.

Anmol Reddy Mekala, Vineeth Dorna, Shreya Dubey, Abhishek Lalwani, David Koleczek, Mukund Rungta, Sadid A. Hasan, Elita A. Lobo

Proceedings of the 31st International Conference on Computational Linguistics, 2025

2024

TAGMol: Target-Aware Gradient-guided Molecule Generation.

Vineeth Dorna, D. Subhalingam, Keshav Kolluru, Shreshth Tuli, Mrityunjay Singh, Saurabh Singal, N. M. Anoop Krishnan, Sayan Ranu

CoRR, 2024

2023

SketchBuddy: Context-Aware Sketch Enrichment and Enhancement.

Aishwarya Agarwal, Anuj Srivastava, Inderjeet Nair, Swasti Shreya Mishra, Vineeth Dorna, Sharmila Reddy Nangi, Balaji Vasan Srinivasan

Proceedings of the 14th Conference on ACM Multimedia Systems, 2023

2022

SPEAR : Semi-supervised Data Programming in Python.

Guttu Sai Abhishek, Harshad Ingole, Parth Laturia, Vineeth Dorna, Ayush Maheshwari, Ganesh Ramakrishnan, Rishabh K. Iyer

Proceedings of the The 2022 Conference on Empirical Methods in Natural Language Processing, 2022