Edited by Charles T. Campbell, University of Washington, Seattle, WA; received June 11, 2024; accepted November 12, 2024 by Editorial Board Member Peter J. Rossky ...

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State Space Models (SSMs) have emerged as efficient alternatives to Transformers, mitigating their quadratic computational cost. However, the application of Parameter-Efficient Fine-Tuning (PEFT) ...

Abstract: Recently, combining the strength of large language models (LLMs) and Evolutionary Computation (EC) has shown promising results for addressing optimization problems. It typically involves ...

Abstract: Through this study, the concept of large language models (LLM) in the context of generative AI has been explored. Gemma-2B, with 4-bit quantization is fine-tuned to bridge the gap between ...