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jingyue zhang

Doctorat - UdeM
Superviseur⋅e principal⋅e
Damien Masson
Co-supervisor
Ian Arawjo
Sujets de recherche
Grands modèles de langage (LLM)
Interaction humain-IA
Systèmes multi-agents

Publications

ChainBuddy: An AI Agent System for Generating LLM Pipelines
jingyue zhang
Ian Arawjo
As large language models (LLMs) advance, their potential applications have grown significantly. However, it remains difficult to evaluate LL… (voir plus)M behavior on user-specific tasks and craft effective pipelines to do so. Many users struggle with where to start, often referred to as the"blank page"problem. ChainBuddy, an AI assistant for generating evaluative LLM pipelines built into the ChainForge platform, aims to tackle this issue. ChainBuddy offers a straightforward and user-friendly way to plan and evaluate LLM behavior, making the process less daunting and more accessible across a wide range of possible tasks and use cases. We report a within-subjects user study comparing ChainBuddy to the baseline interface. We find that when using AI assistance, participants reported a less demanding workload and felt more confident setting up evaluation pipelines of LLM behavior. We derive insights for the future of interfaces that assist users in the open-ended evaluation of AI.
2024-09-20
ArXiv (prépublication)
doi.org
arxiv.org
ChainBuddy: An AI-assisted Agent System for Generating LLM Pipelines
jingyue zhang
Ian Arawjo
2024-09-20
ArXiv (prépublication)
doi.org
arxiv.org
ChainBuddy: An AI-assisted Agent System for Generating LLM Pipelines
jingyue zhang
Ian Arawjo
2024-09-20
ArXiv (prépublication)
doi.org
arxiv.org
ChainBuddy: An AI Agent System for Generating LLM Pipelines
jingyue zhang
Ian Arawjo
2024-01-01
arXiv.org (prépublication)
doi.org
arxiv.org
ChainBuddy: An AI-assisted Agent System for Helping Users Set up LLM Pipelines
jingyue zhang
Ian Arawjo
2024-01-01
UIST (Adjunct Volume) (publié)
doi.org