4 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.AI2025
Orchestrating Agents and Data for Enterprise: A Blueprint Architecture for Compound AI
Eser Kandogan, Nikita Bhutani, Dan Zhang +3
Large language models (LLMs) have gained significant interest in industry due to their impressive capabilities across a wide range of tasks. However, the widespread adoption of LLM…
cs.CL2024★ 4 cited
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…
cs.HC2023★ 2 cited
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…