Exploring Augmentation and Cognitive Strategies for AI based Synthetic Personae
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arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866911842290368512 |
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| author | Gonzalez, Rafael Arias DiPaola, Steve |
| author_facet | Gonzalez, Rafael Arias DiPaola, Steve |
| contents | Large language models (LLMs) hold potential for innovative HCI research, including the creation of synthetic personae. However, their black-box nature and propensity for hallucinations pose challenges. To address these limitations, this position paper advocates for using LLMs as data augmentation systems rather than zero-shot generators. We further propose the development of robust cognitive and memory frameworks to guide LLM responses. Initial explorations suggest that data enrichment, episodic memory, and self-reflection techniques can improve the reliability of synthetic personae and open up new avenues for HCI research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_10890 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Exploring Augmentation and Cognitive Strategies for AI based Synthetic Personae Gonzalez, Rafael Arias DiPaola, Steve Artificial Intelligence Human-Computer Interaction Information Retrieval I.2.7 Large language models (LLMs) hold potential for innovative HCI research, including the creation of synthetic personae. However, their black-box nature and propensity for hallucinations pose challenges. To address these limitations, this position paper advocates for using LLMs as data augmentation systems rather than zero-shot generators. We further propose the development of robust cognitive and memory frameworks to guide LLM responses. Initial explorations suggest that data enrichment, episodic memory, and self-reflection techniques can improve the reliability of synthetic personae and open up new avenues for HCI research. |
| title | Exploring Augmentation and Cognitive Strategies for AI based Synthetic Personae |
| topic | Artificial Intelligence Human-Computer Interaction Information Retrieval I.2.7 |
| url | https://arxiv.org/abs/2404.10890 |