Tahseen Rabbani

According to our database, Tahseen Rabbani authored at least 26 papers between 2020 and 2026.

Collaborative distances:

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

2026

Federation over Text: Insight Sharing for Multi-Agent Reasoning.

Dixi Yao, Tahseen Rabbani, Tian Li

CoRR, April, 2026

Not All Prefills Are Equal: PPD Disaggregation for Multi-turn LLM Serving.

Zongze Li, Jingyu Liu, Zach Xu, Yineng Zhang, Tahseen Rabbani, Ce Zhang

CoRR, March, 2026

Asynchronous Heavy-Tailed Optimization.

Junfei Sun, Dixi Yao, Xuchen Gong, Tahseen Rabbani, Manzil Zaheer, Tian Li

CoRR, February, 2026

Mitigating Unintended Memorization with LoRA in Federated Learning for LLMs.

Thierry Bossy, Julien Tuan Tu Vignoud, Tahseen Rabbani, Juan Ramón Troncoso-Pastoriza, Martin Jaggi

Trans. Mach. Learn. Res., 2026

2025

Hold Onto That Thought: Assessing KV Cache Compression On Reasoning.

Minghui Liu, Aadi Palnitkar, Tahseen Rabbani, Hyunwoo Jae, Kyle Rui Sang, Dixi Yao, Shayan Shabihi, Fuheng Zhao, Tian Li, Ce Zhang, Furong Huang, Kunpeng Zhang

CoRR, December, 2025

DISCO: A Browser-Based Privacy-Preserving Framework for Distributed Collaborative Learning.

Julien Tuan Tu Vignoud, Valérian Rousset, Hugo El Guedj, Ignacio Aleman, Walid Bennaceur, Batuhan Faik Derinbay, Eduard Durech, Damien Gengler, Lucas Giordano, Felix Grimberg, Franziska Lippoldt, Christina Kopidaki, Jiafan Liu, Lauris Lopata, Nathan Maire, Paul Mansat, Martin Milenkoski, Emmanuel Omont, Günes Özgün, Mina Petrovic, Francesco Posa, Morgan Ridel, Giorgio Savini, Marcel Torne, Lucas Trognon, Alyssa Unell, Olena Zavertiaieva, Sai Praneeth Karimireddy, Tahseen Rabbani, Mary-Anne Hartley, Martin Jaggi

CoRR, November, 2025

PRBench: Large-Scale Expert Rubrics for Evaluating High-Stakes Professional Reasoning.

Afra Feyza Akyürek, Advait Gosai, Chen Bo Calvin Zhang, Vipul Gupta, Jaehwan Jeong, Anisha Gunjal, Tahseen Rabbani, Maria Mazzone, David Randolph, Mohammad Mahmoudi Meymand, Gurshaan Chattha, Paula Rodriguez, Diego Mares, Pavit Singh, Michael Liu, Subodh Chawla, Pete Cline, Lucy Ogaz, Ernesto Hernandez, Zihao Wang, Pavi Bhatter, Marcos Ayestaran, Bing Liu, Yunzhong He

CoRR, November, 2025

ResearchRubrics: A Benchmark of Prompts and Rubrics For Evaluating Deep Research Agents.

Manasi Sharma, Chen Bo Calvin Zhang, Chaithanya Bandi, Clinton Wang, Ankit Aich, Huy Nghiem, Tahseen Rabbani, Ye Htet, Brian Jang, Sumana Basu, Aishwarya Balwani, Denis Peskoff, Marcos Ayestaran, Sean M. Hendryx, Brad Kenstler, Bing Liu

CoRR, November, 2025

Remote Labor Index: Measuring AI Automation of Remote Work.

Mantas Mazeika, Alice Gatti, Cristina Menghini, Udari Madhushani Sehwag, Shivam Singhal, Yury Orlovskiy, Steven Basart, Manasi Sharma, Denis Peskoff, Elaine Lau, Jaehyuk Lim, Lachlan Carroll, Alice Blair, Vinaya Sivakumar, Sumana Basu, Brad Kenstler, Yuntao Ma, Julian Michael, Xiaoke Li, Oliver Ingebretsen, Aditya Mehta, Jean Mottola, John Teichmann, Kevin Yu, Zaina Shaik, Adam Khoja, Richard Ren, Jason Hausenloy, Long Phan, Ye Htet, Ankit Aich, Tahseen Rabbani, Vivswan Shah, Andriy Novykov, Felix Binder, Kirill Chugunov, Luis Ramirez, Matias Geralnik, Hernán Mesura, Dean Lee, Ed-Yeremai Hernandez-Cardona, Annette Diamond, Summer Yue, Alexandr Wang, Bing Liu, Ernesto Hernandez, Dan Hendrycks

CoRR, October, 2025

Access Paths for Efficient Ordering with Large Language Models.

Fuheng Zhao, Jiayue Chen, Yiming Pan, Tahseen Rabbani, Divyakant Agrawal, Amr El Abbadi

CoRR, September, 2025

2024

Efficient Models and Learning Strategies for Resource-Constrained Systems.

Tahseen Rabbani

PhD thesis, 2024

HashEvict: A Pre-Attention KV Cache Eviction Strategy using Locality-Sensitive Hashing.

Minghui Liu, Tahseen Rabbani, Tony O'Halloran, Ananth Sankaralingam, Mary-Anne Hartley, Brian J. Gravelle, Furong Huang, Cornelia Fermüller, Yiannis Aloimonos

CoRR, 2024

Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity.

Mucong Ding, Tahseen Rabbani, Bang An, Evan Z. Wang, Furong Huang

CoRR, 2024

Calibrated Dataset Condensation for Faster Hyperparameter Search.

Mucong Ding, Yuancheng Xu, Tahseen Rabbani, Xiaoyu Liu, Brian J. Gravelle, Teresa M. Ranadive, Tai-Ching Tuan, Furong Huang

CoRR, 2024

Benchmarking the Robustness of Image Watermarks.

Bang An, Mucong Ding, Tahseen Rabbani, Aakriti Agrawal, Yuancheng Xu, Chenghao Deng, Sicheng Zhu, Abdirisak Mohamed, Yuxin Wen, Tom Goldstein, Furong Huang

CoRR, 2024

conv_einsum: A Framework for Representation and Fast Evaluation of Multilinear Operations in Convolutional Tensorial Neural Networks.

Tahseen Rabbani, Jiahao Su, Xiaoyu Liu, David Chan, Geoffrey Sangston, Furong Huang

CoRR, 2024

Balancing Label Imbalance in Federated Environments Using Only Mixup and Artificially-Labeled Noise.

Tahseen Rabbani, Kyle Sang, Furong Huang

Proceedings of the Pattern Recognition and Artificial Intelligence, 2024

A Linear Time and Space Local Point Cloud Geometry Encoder via Vectorized Kernel Mixture (VecKM).

Dehao Yuan, Cornelia Fermüller, Tahseen Rabbani, Furong Huang, Yiannis Aloimonos

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

WAVES: Benchmarking the Robustness of Image Watermarks.

Bang An, Mucong Ding, Tahseen Rabbani, Aakriti Agrawal, Yuancheng Xu, Chenghao Deng, Sicheng Zhu, Abdirisak Mohamed, Yuxin Wen, Tom Goldstein, Furong Huang

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

2023

Large-Scale Distributed Learning via Private On-Device Locality-Sensitive Hashing.

Tahseen Rabbani, Marco Bornstein, Furong Huang

CoRR, 2023

Large-Scale Distributed Learning via Private On-Device LSH.

Tahseen Rabbani, Marco Bornstein, Furong Huang

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

SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model Communication.

Marco Bornstein, Tahseen Rabbani, Evan Wang, Amrit S. Bedi, Furong Huang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity.

Mucong Ding, Tahseen Rabbani, Bang An, Evan Wang, Furong Huang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Comfetch: Federated Learning of Large Networks on Memory-Constrained Clients via Sketching.

Tahseen Rabbani, Brandon Yushan Feng, Yifan Yang, Arjun Rajkumar, Amitabh Varshney, Furong Huang

CoRR, 2021

Practical and Fast Momentum-Based Power Methods.

Tahseen Rabbani, Apollo Jain, Arjun Rajkumar, Furong Huang

Proceedings of the Mathematical and Scientific Machine Learning, 2021

2020

Fast GPU Convolution for CP-Decomposed Tensorial Neural Networks.

Alexander Reustle, Tahseen Rabbani, Furong Huang

Proceedings of the Intelligent Systems and Applications, 2020