![Bites of FM4S: [2] LLMs for experiments in fundamental physics](/event/1543967/logo-1303698739.png){kind=logo}
The ATLAS Collaboration is composed of around 6,000 scientists, engineers, developers, students and administrators, with decades of institutional documentation spread across wikis, code docs, meeting agendas, recommendations, publications, tutorials, and project management systems. With the advent of retrieval augmented generation (RAG) and sophisticated large language models (LLMs) such as...
The data processing and analyzing is one of the main
challenges at HEP experiments. To accelerate the physics
analysis and drive new physics discovery, the rapidly
developing Large Language Model (LLM) is the most promising
approach, it have demonstrated astonishing capabilities in
recognition and generation of text while most parts of physics
analysis can be benefitted. In this talk we...
Time-domain astronomy is rapidly entering a data-rich era in which wide-field surveys discover millions of transients per year, overwhelming traditional, hand-driven analysis. In this talk we present SpeakYSE, an agentic and open-source language model that turns natural-language requests into end-to-end analyses for the Young Supernova Experiment. The SpeakYSE links literature retrieval,...
We introduce A2rchi (AI-Augmented Research Chat Intelligence), an intelligent, domain-adaptable open source chatbot designed to support research and education workflows.
Beyond its core functionalities, A2rchi also integrates with common communication and workflow tools, including email systems, ticketing platforms, and collaboration platforms like Mattermost, offering seamless assistance...
