2023.emnlp-demo.14@ACL

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#1 INTELMO: Enhancing Models’ Adoption of Interactive Interfaces [PDF] [Copy] [Kimi2]

Authors: Chunxu Yang ; Chien-Sheng Wu ; Lidiya Murakhovs’ka ; Philippe Laban ; Xiang Chen

This paper presents INTELMO, an easy-to-use library to help model developers adopt user-faced interactive interfaces and articles from real-time RSS sources for their language models. The library categorizes common NLP tasks and provides default style patterns, streamlining the process of creating interfaces with minimal code modifications while ensuring an intuitive user experience. Moreover, INTELMO employs a multi-granular hierarchical abstraction to provide developers with fine-grained and flexible control over user interfaces. INTELMO is under active development, with document available at https://intelmo.github.io.