大模型让科研信息更易获取，助力全民理解科学。
Large Language Models: New Opportunities for Access to Science
- 用大模型增强检索生成，提升科学数据与文献的可访问性。
- 在KM3NeT中应用后，显著简化了科研人员获取信息的流程。
- 适合科研新手、跨领域学者及公众快速理解复杂科学内容。
像ChatGPT这类大语言模型在科学数据、软件和文献的信息检索中的应用，为不同专业水平的人群提供了更简便的科学获取与理解途径。它们不仅能够增强我们正在构建的开放科学环境的可用性，还能帮助系统性地挖掘长期积累的科学文献知识库。以KM3NeT中子探测器的开放科学环境建设为例，展示了增强型检索生成聊天应用的实际应用前景，为大模型在更广泛科学领域的应用提供了示范。
原文摘要 · Abstract (English)
The adaptation of Large Language Models like ChatGPT for information retrieval from scientific data, software and publications is offering new opportunities to simplify access to and understanding of science for persons from all levels of expertise. They can become tools to both enhance the usability of the open science environment we are building as well as help to provide systematic insight to a long-built corpus of scientific publications. The uptake of Retrieval Augmented Generation-enhanced chat applications in the construction of the open science environment of the KM3NeT neutrino detectors serves as a focus point to explore and exemplify prospects for the wider application of Large Language Models for our science.
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