MEGAnno+: A Human-LLM Collaborative Annotation System

Arxiv Link - 2024-02-28 04:58:07

Abstract

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, sociocultural, or domain-specific context, potentially leading to incorrect annotations. Therefore, we advocate a collaborative approach where humans and LLMs work together to produce reliable and high-quality labels. We present MEGAnno+, a human-LLM collaborative annotation system that offers effective LLM agent and annotation management, convenient and robust LLM annotation, and exploratory verification of LLM labels by humans.

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🚀 Exciting News in AI and NLP! 🚀 As large language models (LLMs) continue to revolutionize the field of Natural Language Processing (NLP), a critical discussion emerges on the importance of combining human expertise with machine efficiency. While LLMs excel in rapid and cost-effective data labeling, their limitations in grasping intricate social, cultural, or domain-specific nuances may result in inaccuracies. Introducing MEGAnno+ - a cutting-edge human-LLM collaborative annotation system designed to enhance the accuracy and quality of labeled data. By leveraging the strengths of both humans and LLMs, MEGAnno+ offers efficient LLM agent and annotation management, robust annotation processes, and human verification to ensure precise labeling. Discover how collaborative efforts between humans and LLMs can elevate the standard of data annotation and drive impactful advancements in AI and NLP. Dive into the details of MEGAnno+ here: Read more #AI #NLP #Collaboration #DataAnnotation #MEGAnno+ #TechInnovation 🌟

🚀 Exciting research alert! Large language models (#LLMs) are speeding up data labeling, but may lack nuanced understanding. Check out MEGAnno+, a collaborative human-LLM annotation system for reliable labels. Dive into the details here: http://arxiv.org/abs/2402.18050v1 #NLP #AI

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