@inproceedings{yang-etal-2023-intelmo,
title = "{INTELMO}: Enhancing Models{'} Adoption of Interactive Interfaces",
author = "Yang, Chunxu and
Wu, Chien-Sheng and
Murakhovs{'}ka, Lidiya and
Laban, Philippe and
Chen, Xiang",
editor = "Feng, Yansong and
Lefever, Els",
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.emnlp-demo.14",
doi = "10.18653/v1/2023.emnlp-demo.14",
pages = "161--166",
abstract = "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 \url{https://intelmo.github.io}.",
}
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<abstract>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.</abstract>
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%0 Conference Proceedings
%T INTELMO: Enhancing Models’ Adoption of Interactive Interfaces
%A Yang, Chunxu
%A Wu, Chien-Sheng
%A Murakhovs’ka, Lidiya
%A Laban, Philippe
%A Chen, Xiang
%Y Feng, Yansong
%Y Lefever, Els
%S Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F yang-etal-2023-intelmo
%X 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.
%R 10.18653/v1/2023.emnlp-demo.14
%U https://aclanthology.org/2023.emnlp-demo.14
%U https://doi.org/10.18653/v1/2023.emnlp-demo.14
%P 161-166
Markdown (Informal)
[INTELMO: Enhancing Models’ Adoption of Interactive Interfaces](https://aclanthology.org/2023.emnlp-demo.14) (Yang et al., EMNLP 2023)
ACL
- Chunxu Yang, Chien-Sheng Wu, Lidiya Murakhovs’ka, Philippe Laban, and Xiang Chen. 2023. INTELMO: Enhancing Models’ Adoption of Interactive Interfaces. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 161–166, Singapore. Association for Computational Linguistics.