4 citations · 7 across the 4 of their papers we have counts for
4 papers
MEGAnno+: A Human-LLM Collaborative Annotation System
Hannah Kim, Kushan Mitra, Rafael Li Chen +2
Large language models (LLMs) can label data faster and cheaper than humans for various NLP tasks. Despite their prowess, LLMs may fall short in understanding of complex, sociocultu…
Knowledge Acquisition and Integration with Expert-in-the-loop
Sajjadur Rahman, Frederick Choi, Hannah Kim +2
Constructing and serving knowledge graphs (KGs) is an iterative and human-centered process involving on-demand programming and analysis. In this paper, we present Kyurem, a program…
Towards Multifaceted Human-Centered AI
Sajjadur Rahman, Hannah Kim, Dan Zhang +2
Human-centered AI workflows involve stakeholders with multiple roles interacting with each other and automated agents to accomplish diverse tasks. In this paper, we call for a holi…
MEGAnno: Exploratory Labeling for NLP in Computational Notebooks
Dan Zhang, Hannah Kim, Rafael Li Chen +2
We present MEGAnno, a novel exploratory annotation framework designed for NLP researchers and practitioners. Unlike existing labeling tools that focus on data labeling only, our fr…