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168 Publications

2026 | Published | Thesis | PhD | IST-REx-ID: 21854 | OA
On the utility and effects of efficiency in artificial neural networks
E.B. Iofinova, On the Utility and Effects of Efficiency in Artificial Neural Networks, Institute of Science and Technology Austria, 2026.
[Published Version] View | Files available | DOI
 
2026 | Published | Conference Poster | IST-REx-ID: 21857 | OA
Panza: Investigating the feasibility of fully-local personalized text generation
A. Nicolicioiu, E.B. Iofinova, A. Jovanovic, E. Kurtic, M. Nikdan, A. Panferov, I. Markov, N. Shavit, D.-A. Alistarh, Panza: Investigating the Feasibility of Fully-Local Personalized Text Generation, OpenReview, 2026.
[Accepted Version] View | Files available | Download Accepted Version (ext.)
 
2026 | Draft | Preprint | IST-REx-ID: 21859 | OA
Behemoth: Benchmarking unlearning in LLMs using fully synthetic data
E.B. Iofinova, D.-A. Alistarh, ArXiv (n.d.).
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 19877 | OA
MARLIN: Mixed-precision auto-regressive parallel inference on Large Language Models
E. Frantar, R.L. Castro, J. Chen, T. Hoefler, D.-A. Alistarh, in:, Proceedings of the 30th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2025, pp. 239–251.
[Published Version] View | Files available | DOI | WoS | arXiv
 
2025 | Published | Journal Article | IST-REx-ID: 19969 | OA | PlanS
Near-optimal leader election in population protocols on graphs
D.-A. Alistarh, J. Rybicki, S. Voitovych, Distributed Computing 38 (2025) 207–245.
[Published Version] View | Files available | DOI | WoS | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 20032 | OA
Scalable mechanistic neural networks
J. Chen, D. Yao, A.A. Pervez, D.-A. Alistarh, F. Locatello, in:, 13th International Conference on Learning Representations, ICLR, 2025, pp. 63716–63737.
[Published Version] View | Files available | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 20034 | OA
LDAdam: Adaptive optimization from low-dimensional gradient statistics
T. Robert, M. Safaryan, I.-V. Modoranu, D.-A. Alistarh, in:, 13th International Conference on Learning Representations, ICLR, 2025, pp. 101877–101913.
[Published Version] View | Files available | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 20037 | OA
Wasserstein distances, neuronal entanglement, and sparsity
S. Sawmya, L. Kong, I. Markov, D.-A. Alistarh, N. Shavit, in:, 13th International Conference on Learning Representations, ICLR, 2025, pp. 26244–26274.
[Published Version] View | Files available | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 20038 | OA
The journey matters: Average parameter count over pre-training unifies sparse and dense scaling laws
T. Jin, A.I. Humayun, U. Evci, S. Subramanian, A. Yazdanbakhsh, D.-A. Alistarh, G.K. Dziugaite, in:, 13th International Conference on Learning Representations, ICLR, 2025, pp. 85165–85181.
[Published Version] View | Files available | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 20224 | OA
In the search of optimal tree networks: Hardness and heuristics
P. Martynov, M. Buzdalov, S. Pankratov, V. Aksenov, S. Schmid, in:, Proceedings of the 2025 Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2025, pp. 249–257.
[Published Version] View | Files available | DOI | WoS
 
2025 | Published | Conference Paper | IST-REx-ID: 20684 | OA
“Give me BF16 or give me death”? Accuracy-performance trade-offs in LLM quantization
E. Kurtic, A. Marques, S. Pandit, M. Kurtz, D.-A. Alistarh, in:, Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics, Association for Computational Linguistics, 2025, pp. 26872–26886.
[Published Version] View | Files available | arXiv
 
2025 | Published | Journal Article | IST-REx-ID: 20704
Scalable multitemperature free energy sampling of classical Ising spin states
P. Tuo, Z. Zeng, J. Chen, B. Cheng, Journal of Chemical Theory and Computation 21 (2025) 11427–11435.
View | Files available | DOI | WoS | PubMed | Europe PMC
 
2025 | Published | Journal Article | IST-REx-ID: 19713 | OA
Hybrid decentralized optimization: Leveraging both first- and zeroth-order optimizers for faster convergence
S. Talaei, M. Ansaripour, G. Nadiradze, D.-A. Alistarh, Proceedings of the 39th AAAI Conference on Artificial Intelligence 39 (2025) 20778–20786.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 20820 | OA
EvoPress: Accurate dynamic model compression via evolutionary search
O. Sieberling, D. Kuznedelev, E. Kurtic, D.-A. Alistarh, in:, 42nd International Conference on Machine Learning, ML Research Press, 2025, pp. 55556–55590.
[Published Version] View | Files available | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 20821 | OA
Layer-wise quantization for quantized optimistic dual averaging
A.D. Nguyen, I. Markov, F.Z. Wu, A. Ramezani-Kebrya, K. Antonakopoulos, D.-A. Alistarh, V. Cevher, in:, 42nd International Conference on Machine Learning, ML Research Press, 2025, pp. 46026–46072.
[Published Version] View | Files available | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 21250 | OA
An almost-logarithmic lower bound for leader election with bounded value contention
D.-A. Alistarh, F. Ellen, A. Fedorov, in:, 39th International Symposium on Distributed Computing, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2025, p. 3:1-3:16.
[Published Version] View | Files available | DOI
 
2025 | Published | Book Chapter | IST-REx-ID: 21257 | OA
Sparse Fine-Tuning for Inference Acceleration of Large Language Models
E. Kurtic, D. Kuznedelev, E. Frantar, M. Goinv, S. Pandit, A. Agarwalla, T. Nguyen, A. Marques, M. Kurtz, D.-A. Alistarh, in:, P. Passban, A. Way, M. Rezagholizadeh (Eds.), Enhancing LLM Performance. Efficacy, Fine-Tuning, and Inference Techniques, Springer Nature, 2025, pp. 83–97.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2025 | Draft | Preprint | IST-REx-ID: 21858 | OA
Position: It's time to act on the risk of efficient personalized text generation
E.B. Iofinova, A. Jovanovic, D.-A. Alistarh, ArXiv (n.d.).
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 18070
Federated SGD with local asynchrony
B. Chatterjee, V. Kungurtsev, D.-A. Alistarh, in:, Proceedings of the 44th International Conference on Distributed Computing Systems, IEEE, 2024, pp. 857–868.
View | DOI | WoS
 
2024 | Published | Conference Paper | IST-REx-ID: 18113 | OA
Extreme compression of large language models via additive quantization
V. Egiazarian, A. Panferov, D. Kuznedelev, E. Frantar, A. Babenko, D.-A. Alistarh, in:, Proceedings of the 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 12284–12303.
[Preprint] View | Download Preprint (ext.) | arXiv
 

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