5 citations · 15 across the 7 of their papers we have counts for
7 papers
Spec-Driven AI for Science: The ARIA Framework for Automated and Reproducible Data Analysis
Chuke Chen, Biao Luo, Nan Li +4
The rapid expansion of scientific data has widened the gap between analytical capability and research intent. Existing AI-based analysis tools, ranging from AutoML frameworks to ag…
Environmental large language model Evaluation (ELLE) dataset: A Benchmark for Evaluating Generative AI applications in Eco-environment Domain
Jing Guo, Nan Li, Ming Xu
Generative AI holds significant potential for ecological and environmental applications such as monitoring, data analysis, education, and policy support. However, its effectiveness…
A Method for Parsing and Vectorization of Semi-structured Data used in Retrieval Augmented Generation
Hang Yang, Jing Guo, Jianchuan Qi +5
This paper presents a novel method for parsing and vectorizing semi-structured data to enhance the functionality of Retrieval-Augmented Generation (RAG) within Large Language Model…
Molecule Design by Latent Prompt Transformer
Deqian Kong, Yuhao Huang, Jianwen Xie +8
This work explores the challenging problem of molecule design by framing it as a conditional generative modeling task, where target biological properties or desired chemical constr…
Advanced Unstructured Data Processing for ESG Reports: A Methodology for Structured Transformation and Enhanced Analysis
Jiahui Peng, Jing Gao, Xin Tong +6
In the evolving field of corporate sustainability, analyzing unstructured Environmental, Social, and Governance (ESG) reports is a complex challenge due to their varied formats and…
Empowering Working Memory for Large Language Model Agents
Jing Guo, Nan Li, Jianchuan Qi +5
Large language models (LLMs) have achieved impressive linguistic capabilities. However, a key limitation persists in their lack of human-like memory faculties. LLMs exhibit constra…
Molecule Design by Latent Prompt Transformer
Deqian Kong, Yuhao Huang, Jianwen Xie +1
This paper proposes a latent prompt Transformer model for solving challenging optimization problems such as molecule design, where the goal is to find molecules with optimal values…