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ChatGPT-powered Conversational Drug Editing Using Retrieval and Domain . . . To bridge this gap, we propose ChatDrug, a framework to facilitate the systematic investigation of drug editing using LLMs ChatDrug jointly leverages a prompt module, a retrieval and domain feedback (ReDF) module, and a conversation module to streamline effective drug editing
Conversational Drug Editing Using Retrieval and Domain Feedback ChatDrug jointly leverages a prompt module, a retrieval and domain feedback module, and a conversation module to streamline effective drug editing We empirically show that ChatDrug reaches the best performance on all 39 drug editing tasks, encompassing small molecules, peptides, and proteins
ChatGPT-powered Conversational Drug Editing Using Retrieval and Domain . . . ChatDrug jointly leverages a prompt module, a retrieval and domain feedback module, and a conversation module to streamline effective drug editing We empirically show that ChatDrug reaches the best performance on 33 out of 39 drug editing tasks, encompassing small molecules, pep-tides, and proteins
GitHub - chao1224 ChatDrug: LLM for Drug Editing, ICLR 2024 ChatDrug is for conversational drug editing, and three types of drugs are considered: Setup the anaconda (skip this if you already have conda) export PATH= $PWD anaconda3 bin: $PATH Then download the required python packages: pip install -e We provide the dataset in this link
Conversational Drug Editing Using Retrieval and Domain Feedback ChatDrug jointly leverages a prompt module, a retrieval and domain feedback module, and a conversation module to streamline effective drug editing We empirically show that ChatDrug reaches the best performance on all 39 drug editing tasks, encompassing small molecules, peptides, and proteins
ChatGPT-powered Conversational Drug Editing Using Retrieval and Domain . . . To bridge this gap, we propose ChatDrug, a framework to facilitate the systematic investigation of drug editing using LLMs ChatDrug jointly leverages a prompt module, a retrieval and domain feedback (ReDF) module, and a conversation module to streamline effective drug editing
ChatGPT-powered Conversational Drug Editing - GitHub Pages ChatGPT-powered Conversational Drug Editing Using Retrieval and Domain Feedback Shengchao Liu 1,2 ♠ Jiongxiao Wang 3 ♠ Yijin Yang 3 Chengpeng Wang 4 Ling Liu 5 Hongyu Guo 6 ♦ Chaowei Xiao 3 ♦ 1 Mila 2 Université de Montréal 3 Arizona State University 4 University of Illinois Urbana-Champaign 5 Princeton University 6 National Research
ChatGPT-powered Conversational Drug Editing Using Retrieval and Domain . . . To bridge this gap, we propose ChatDrug, a framework to facilitate the systematic investigation of drug editing using LLMs ChatDrug jointly leverages a prompt module, a retrieval and domain feedback (ReDF) module, and a conversation module to streamline effective drug editing
ChatDrug README. md at main · chao1224 ChatDrug · GitHub For protein editing tasks, multiple evaluation times in retrieval process would consume a lot of time Thus, we provide a fast version of conversation setting Running the following command to implement accelerate ChatDrug for protein editing tasks: We also provide code for In-Context Learning setting: