An LLM-based topic modeling method with a custom evaluation framework improves topic interpretability, specificity, and polarity consistency over prior approaches when linking corporate review text to external outcomes such as employee morale.
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LLM reasoning refines unsupervised text clusters via coherence checks, redundancy removal, and label grounding, yielding better coherence and human-aligned labels on social media data.
Large-scale review mining of 1M+ comments from 171 Gen-AI apps using an LLM framework reveals top topics plus three opportunities and three challenges for developers.
VIDEE introduces a human-in-the-loop system using Monte-Carlo Tree Search for task decomposition, executable pipeline generation, and LLM-based evaluation with visualizations to support non-expert text analytics.
Survey and chat data from CharacterAI users link companionship-focused AI use to lower well-being, with stronger ties for users who have small offline networks and engage intensively or disclosively.
citing papers explorer
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Proposing Topic Models and Evaluation Frameworks for Analyzing Associations with External Outcomes: An Application to Leadership Analysis Using Large-Scale Corporate Review Data
An LLM-based topic modeling method with a custom evaluation framework improves topic interpretability, specificity, and polarity consistency over prior approaches when linking corporate review text to external outcomes such as employee morale.
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Reasoning-Based Refinement of Unsupervised Text Clusters with LLMs
LLM reasoning refines unsupervised text clusters via coherence checks, redundancy removal, and label grounding, yielding better coherence and human-aligned labels on social media data.
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Understanding the Challenges and Opportunities of Generative AI Apps: An Empirical Study
Large-scale review mining of 1M+ comments from 171 Gen-AI apps using an LLM framework reveals top topics plus three opportunities and three challenges for developers.
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VIDEE: Visual and Interactive Decomposition, Execution, and Evaluation of Text Analytics with Intelligent Agents
VIDEE introduces a human-in-the-loop system using Monte-Carlo Tree Search for task decomposition, executable pipeline generation, and LLM-based evaluation with visualizations to support non-expert text analytics.
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The Rise of AI Companions: Interaction with AI Companions and Psychological Well-being
Survey and chat data from CharacterAI users link companionship-focused AI use to lower well-being, with stronger ties for users who have small offline networks and engage intensively or disclosively.