most citedTnT-LLM: Text Mining at Scale with Large Language Models

2 citations · 4 across the 3 of their papers we have counts for

collaborators

3 papers

cs.AI2024

BAPO: Base-Anchored Preference Optimization for Overcoming Forgetting in Large Language Models Personalization

Gihun Lee, Minchan Jeong, Yujin Kim +4

While learning to align Large Language Models (LLMs) with human preferences has shown remarkable success, aligning these models to meet the diverse user preferences presents furthe…

cs.CL2024★ 2 cited

TnT-LLM: Text Mining at Scale with Large Language Models

Mengting Wan, Tara Safavi, Sujay Kumar Jauhar +11

Transforming unstructured text into structured and meaningful forms, organized by useful category labels, is a fundamental step in text mining for downstream analysis and applicati…

cs.CL2024★ 2 cited

Leveraging Large Language Models for Hybrid Workplace Decision Support

Yujin Kim, Chin-Chia Hsu

Large Language Models (LLMs) hold the potential to perform a variety of text processing tasks and provide textual explanations for proposed actions or decisions. In the era of hybr…