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cs.CL2026
More Value per Key: Asymmetric Sparse Attention for Faster LLM Decoding
Noam Elata, Itay Lamprecht, Mikey Shechter +3
Autoregressive generation in Large Language Models (LLMs) is constrained by the memory and computational demands of attention mechanisms. Sparse attention methods mitigate this cos…
cs.CL2025
Toward Cybersecurity-Expert Small Language Models
Matan Levi, Daniel Ohayon, Ariel Blobstein +3
Large language models (LLMs) are transforming everyday applications, yet deployment in cybersecurity lags due to a lack of high-quality, domain-specific models and training dataset…
cs.CL2024
CyberPal.AI: Empowering LLMs with Expert-Driven Cybersecurity Instructions
Matan Levi, Yair Alluouche, Daniel Ohayon +1
Large Language Models (LLMs) have significantly advanced natural language processing (NLP), providing versatile capabilities across various applications. However, their application…