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cs.LG2025
ShiQ: Bringing back Bellman to LLMs
Pierre Clavier, Nathan Grinsztajn, Raphael Avalos +8
The fine-tuning of pre-trained large language models (LLMs) using reinforcement learning (RL) is generally formulated as direct policy optimization. This approach was naturally fav…
cs.LG2021★ 20 cited
Sparsified Secure Aggregation for Privacy-Preserving Federated Learning
Irem Ergun, Hasin Us Sami, Basak Guler
Secure aggregation is a popular protocol in privacy-preserving federated learning, which allows model aggregation without revealing the individual models in the clear. On the other…