AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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The results support adaptive source selection as a useful strategy for molecular prediction under strong structural distribution shifts and support adaptive source selection as a useful strategy for molecular prediction under strong structural distribution shifts.
Recently, Large Language Models (LLMs) have become the dominant paradigm for molecular editing due to their strong generalization capabilities across diverse tasks. However, treating molecules as 1D text strings (SMILES) introduces significant challenges in controllability and structural validity. In this paper, we que...
Evidence of cross-lingual efficacy of code-based LLMs for Chinese QA tasks, further enhanced through Code Llama-M's expanded Chinese vocabulary is found, and successful application of the fine-tuned LLM in a live assistant system, enhancing user experience is demonstrated.
This paper proposes UniEdit, a Unified Graph-based Mixture-of-Experts (MoE) Molecular Editing model that offers a robust alternative to LLMs and incorporates a Mixture-of-Experts architecture that dynamically routes tasks to specialized components.
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