This survey aims to systematically address resource efficiency challenges of Large Language Models by reviewing a broad spectrum of techniques designed to enhance the resource efficiency of LLMs, and introduces a nuanced categorization of resource efficiency techniques by their specific resource types.
Cell type standardization plays a central role in integrating biological knowledge across single-cell studies. While standardized resources (e.g., Cell Ontology, Nomenclature Frameworks) provide unified vocabularies of cell populations, scientific publications and public datasets continue to use heterogeneous study-spe...
Peng Xie, Rongjia Zhou, Zhi-Li Ou et al.· arXiv.org· 0 citations
This survey aims to systematically address resource efficiency challenges in Large Language Models by reviewing a broad spectrum of techniques designed to enhance the resource efficiency of LLMs, and introduces a nuanced categorization of resource efficiency techniques by their specific resource types.
DiffPro, a novel framework that integrates a Latent Diffusion Model (LDM) as a structural prior, confirms that the diffusion prior successfully regularizes the latent space, mitigating task representation collapse and enabling robust, high-precision predictions for combination therapy design.
Shu-Ting Jin, Xu Guo, An-Qi Huang et al.· Proceedings of the 32nd ACM...· 0 citations
LLMBDC (Large Language Model for Biological Domains Oriented Clustering of Gene Ontology) provides a scalable, reproducible, and interpretable route to context-aware, system-level interpretation of GO enrichment results while preserving biological specificity.
Xi-Ming Ran, Jie Xu, Peng Jin et al.· 0 citations
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