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164 Publications
2025 |
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Conference Paper |
IST-REx-ID: 19877 |
Frantar, Elias, Roberto L. Castro, Jiale Chen, Torsten Hoefler, and Dan-Adrian Alistarh. “MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models.” In Proceedings of the 30th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, 239–51. Association for Computing Machinery, 2025. https://doi.org/10.1145/3710848.3710871.
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| arXiv
2025 |
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Journal Article |
IST-REx-ID: 19969 |
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Alistarh, Dan-Adrian, Joel Rybicki, and Sasha Voitovych. “Near-Optimal Leader Election in Population Protocols on Graphs.” Distributed Computing. Springer Nature, 2025. https://doi.org/10.1007/s00446-025-00487-7.
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| arXiv
2025 |
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Conference Paper |
IST-REx-ID: 20032 |
Chen, Jiale, Dingling Yao, Adeel A Pervez, Dan-Adrian Alistarh, and Francesco Locatello. “Scalable Mechanistic Neural Networks.” In 13th International Conference on Learning Representations, 63716–37. ICLR, 2025.
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| arXiv
2025 |
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Conference Paper |
IST-REx-ID: 20034 |
Robert, Thomas, Mher Safaryan, Ionut-Vlad Modoranu, and Dan-Adrian Alistarh. “LDAdam: Adaptive Optimization from Low-Dimensional Gradient Statistics.” In 13th International Conference on Learning Representations, 101877–913. ICLR, 2025.
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| arXiv
2025 |
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Conference Paper |
IST-REx-ID: 20037 |
Sawmya, Shashata, Linghao Kong, Ilia Markov, Dan-Adrian Alistarh, and Nir Shavit. “Wasserstein Distances, Neuronal Entanglement, and Sparsity.” In 13th International Conference on Learning Representations, 26244–74. ICLR, 2025.
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| arXiv
2025 |
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Conference Paper |
IST-REx-ID: 20038 |
Jin, Tian, Ahmed Imtiaz Humayun, Utku Evci, Suvinay Subramanian, Amir Yazdanbakhsh, Dan-Adrian Alistarh, and Gintare Karolina Dziugaite. “The Journey Matters: Average Parameter Count over Pre-Training Unifies Sparse and Dense Scaling Laws.” In 13th International Conference on Learning Representations, 85165–81. ICLR, 2025.
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| arXiv
2025 |
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Conference Paper |
IST-REx-ID: 20224 |
Martynov, Pavel, Maxim Buzdalov, Sergei Pankratov, Vitaliy Aksenov, and Stefan Schmid. “In the Search of Optimal Tree Networks: Hardness and Heuristics.” In Proceedings of the 2025 Genetic and Evolutionary Computation Conference, 249–57. Association for Computing Machinery, 2025. https://doi.org/10.1145/3712256.3726425.
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2025 |
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Conference Paper |
IST-REx-ID: 20684 |
Kurtic, Eldar, Alexandre Marques, Shubhra Pandit, Mark Kurtz, and Dan-Adrian Alistarh. “‘Give Me BF16 or Give Me Death’? Accuracy-Performance Trade-Offs in LLM Quantization.” In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics, 26872–86. Association for Computational Linguistics, 2025.
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| arXiv
2025 |
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Journal Article |
IST-REx-ID: 20704
Tuo, Ping, Zezhu Zeng, Jiale Chen, and Bingqing Cheng. “Scalable Multitemperature Free Energy Sampling of Classical Ising Spin States.” Journal of Chemical Theory and Computation. American Chemical Society, 2025. https://doi.org/10.1021/acs.jctc.5c01248.
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| PubMed | Europe PMC
2025 |
Published |
Journal Article |
IST-REx-ID: 19713 |
Talaei, Shayan, Matin Ansaripour, Giorgi Nadiradze, and Dan-Adrian Alistarh. “Hybrid Decentralized Optimization: Leveraging Both First- and Zeroth-Order Optimizers for Faster Convergence.” Proceedings of the 39th AAAI Conference on Artificial Intelligence. Association for the Advancement of Artificial Intelligence, 2025. https://doi.org/10.1609/aaai.v39i19.34290.
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| arXiv
2025 |
Published |
Conference Paper |
IST-REx-ID: 20820 |
Sieberling, Oliver, Denis Kuznedelev, Eldar Kurtic, and Dan-Adrian Alistarh. “EvoPress: Accurate Dynamic Model Compression via Evolutionary Search.” In 42nd International Conference on Machine Learning, 267:55556–90. ML Research Press, 2025.
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| arXiv
2025 |
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Conference Paper |
IST-REx-ID: 20821 |
Nguyen, Anh Duc, Ilia Markov, Frank Zhengqing Wu, Ali Ramezani-Kebrya, Kimon Antonakopoulos, Dan-Adrian Alistarh, and Volkan Cevher. “Layer-Wise Quantization for Quantized Optimistic Dual Averaging.” In 42nd International Conference on Machine Learning, 267:46026–72. ML Research Press, 2025.
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| arXiv
2025 |
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Conference Paper |
IST-REx-ID: 21250 |
Alistarh, Dan-Adrian, Faith Ellen, and Alexander Fedorov. “An Almost-Logarithmic Lower Bound for Leader Election with Bounded Value Contention.” In 39th International Symposium on Distributed Computing, 356:3:1-3:16. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2025. https://doi.org/10.4230/LIPIcs.DISC.2025.3.
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2025 |
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Book Chapter |
IST-REx-ID: 21257 |
Kurtic, Eldar, Denis Kuznedelev, Elias Frantar, Michael Goinv, Shubhra Pandit, Abhinav Agarwalla, Tuan Nguyen, Alexandre Marques, Mark Kurtz, and Dan-Adrian Alistarh. “Sparse Fine-Tuning for Inference Acceleration of Large Language Models.” In Enhancing LLM Performance. Efficacy, Fine-Tuning, and Inference Techniques, edited by Peyman Passban, Andy Way, and Mehdi Rezagholizadeh, 83–97. Springer Nature, 2025. https://doi.org/10.1007/978-3-031-85747-8_6.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18061 |
Frantar, Elias, and Dan-Adrian Alistarh. “QMoE: Sub-1-Bit Compression of Trillion Parameter Models.” In Proceedings of Machine Learning and Systems, edited by P. Gibbons, G. Pekhimenko, and C. De Sa, Vol. 6, 2024.
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2024 |
Published |
Conference Paper |
IST-REx-ID: 18062 |
Frantar, Elias, Carlos Riquelme Ruiz, Neil Houlsby, Dan-Adrian Alistarh, and Utku Evci. “Scaling Laws for Sparsely-Connected Foundation Models.” In The Twelfth International Conference on Learning Representations, 2024.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18070
Chatterjee, Bapi, Vyacheslav Kungurtsev, and Dan-Adrian Alistarh. “Federated SGD with Local Asynchrony.” In Proceedings of the 44th International Conference on Distributed Computing Systems, 857–68. IEEE, 2024. https://doi.org/10.1109/ICDCS60910.2024.00084.
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2024 |
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Conference Paper |
IST-REx-ID: 18113 |
Egiazarian, Vage, Andrei Panferov, Denis Kuznedelev, Elias Frantar, Artem Babenko, and Dan-Adrian Alistarh. “Extreme Compression of Large Language Models via Additive Quantization.” In Proceedings of the 41st International Conference on Machine Learning, 235:12284–303. ML Research Press, 2024.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18117 |
Nikdan, Mahdi, Soroush Tabesh, Elvir Crncevic, and Dan-Adrian Alistarh. “RoSA: Accurate Parameter-Efficient Fine-Tuning via Robust Adaptation.” In Proceedings of the 41st International Conference on Machine Learning, 235:38187–206. ML Research Press, 2024.
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| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 18121 |
Moakhar, Arshia Soltani, Eugenia B Iofinova, Elias Frantar, and Dan-Adrian Alistarh. “SPADE: Sparsity-Guided Debugging for Deep Neural Networks.” In Proceedings of the 41st International Conference on Machine Learning, 235:45955–87. ML Research Press, 2024.
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| arXiv