From Conversational Web to Inclusive Conversations with LLMs
Article No.: 87, Pages 1 - 3
Abstract
This paper explores how a library of conversational patterns defined for Web browsing can be adopted to improve the accessibility of prompt interfaces for Large Language Models. It reports preliminary findings from a formative evaluation with blind and visually impaired users. It also discusses how these findings support transferring the benefits of voice-based Web browsing to the inclusivity of prompt-based interfaces.
References
[1]
Marcos Baez, Cinzia Cappiello, Claudia M Cutrupi, Maristella Matera, Isabella Possaghi, Emanuele Pucci, Gianluca Spadone, and Antonella Pasquale. 2022. Supporting Natural Language Interaction with the Web. In International Conference on Web Engineering. Springer, 383–390.
[2]
Marcos Baez, Florian Daniel, and Fabio Casati. 2020. Conversational Web Interaction: Proposal of a Dialog-Based Natural Language Interaction Paradigm for the Web. 94–110.
[3]
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, 2020. Language models are few-shot learners. Advances in neural information processing systems 33 (2020), 1877–1901.
[4]
Yung-Ju Chang, Chu-Yuan Yang, Ying-Hsuan Kuo, Wen-Hao Cheng, Chun-Liang Yang, Fang-Yu Lin, I-Hui Yeh, Chih-Kuan Hsieh, Ching-Yu Hsieh, and Yu-Shuen Wang. 2019. Tourgether: Exploring Tourists’ Real-time Sharing of Experiences as a Means of Encouraging Point-of-Interest Exploration. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 3, 4 (2019), 128:1–128:25. https://doi.org/10.1145/3369832
[5]
Hai Dang, Lukas Mecke, Florian Lehmann, Sven Goller, and Daniel Buschek. 2022. How to prompt? Opportunities and challenges of zero-and few-shot learning for human-AI interaction in creative applications of generative models. arXiv preprint arXiv:2209.01390 (2022).
[6]
Christoph Leiter, Ran Zhang, Yanran Chen, Jonas Belouadi, Daniil Larionov, Vivian Fresen, and Steffen Eger. 2023. Chatgpt: A meta-analysis after 2.5 months. arXiv preprint arXiv:2302.13795 (2023).
[7]
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2023. Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing. Comput. Surveys 55, 9 (2023), 1–35.
[8]
Jimmie Manning. 2017. In vivo coding. The international encyclopedia of communication research methods 24 (2017), 1–2.
[9]
Ben Pietrzak, Ben Swanson, Kory Mathewson, Monica Dinculescu, and Sherol Chen. 2021. Story Centaur: Large Language Model Few Shot Learning as a Creative Writing Tool. (2021).
[10]
Alisha Pradhan, Kanika Mehta, and Leah Findlater. 2018. " Accessibility Came by Accident" Use of Voice-Controlled Intelligent Personal Assistants by People with Disabilities. In CHI 2018. 1–13.
[11]
Emanuele Pucci, Isabella Possaghi, Claudia Maria Cutrupi, Marcos Báez, Cinzia Cappiello, and Maristella Matera. 2023. Defining Patterns for a Conversational Web. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, CHI 2023, Hamburg, Germany, April 23-28, 2023, Albrecht Schmidt, Kaisa Väänänen, Tesh Goyal, Per Ola Kristensson, Anicia Peters, Stefanie Mueller, Julie R. Williamson, and Max L. Wilson (Eds.). ACM, 118:1–118:17. https://doi.org/10.1145/3544548.3581145
[12]
Victor Sanh, Albert Webson, Colin Raffel, Stephen H Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Teven Le Scao, Arun Raja, 2021. Multitask prompted training enables zero-shot task generalization. arXiv preprint arXiv:2110.08207 (2021).
[13]
Hendrik Strobelt, Albert Webson, Victor Sanh, Benjamin Hoover, Johanna Beyer, Hanspeter Pfister, and Alexander M Rush. 2022. Interactive and visual prompt engineering for ad-hoc task adaptation with large language models. IEEE transactions on visualization and computer graphics 29, 1 (2022), 1146–1156.
[14]
Ziwei Xu, Sanjay Jain, and Mohan Kankanhalli. 2024. Hallucination is inevitable: An innate limitation of large language models. arXiv preprint arXiv:2401.11817 (2024).
[15]
JD Zamfirescu-Pereira, Richmond Y Wong, Bjoern Hartmann, and Qian Yang. 2023. Why Johnny can’t prompt: how non-AI experts try (and fail) to design LLM prompts. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. 1–21.
[16]
John Zimmerman, Jodi Forlizzi, and Shelley Evenson. 2007. Research through design as a method for interaction design research in HCI. In Proceedings of the SIGCHI conference on Human factors in computing systems. 493–502.
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June 2024
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Association for Computing Machinery
New York, NY, United States
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Published: 03 June 2024
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AVI 2024
AVI 2024: International Conference on Advanced Visual Interfaces 2024
June 3 - 7, 2024
Arenzano, Genoa, Italy
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AVI '24 Paper Acceptance Rate 21 of 82 submissions, 26%;
Overall Acceptance Rate 128 of 490 submissions, 26%
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