Savvas Petridis
Hi! I'm a visiting researcher in PAIR -- researching how to make large language models useful for everyone, from investigative journalists to designers.
Here is my personal website: https://savvaspetridis.github.io/
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Visualizing Linguistic Diversity of Text Datasets Synthesized by Large Language Models
IEEE Conference on Visualization and Visual Analytics (VIS), IEEE (2023)
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Large language models (LLMs) can be used to generate smaller, more refined datasets via few-shot prompting for benchmarking, fine-tuning or other use cases. However, understanding and evaluating these datasets is difficult, and the failure modes of LLM-generated data are still not well understood. Specifically, the data can be repetitive in surprising ways, not only semantically but also syntactically and lexically. We present LinguisticLens, a novel interactive visualization tool for making sense of and analyzing syntactic diversity of LLM-generated datasets. LinguisticLens clusters text along syntactic, lexical, and semantic axes. It supports hierarchical visualization of a text dataset, allowing users to quickly scan for an overview and inspect individual examples. The live demo is available at https://shorturl.at/zHOUV.
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PromptInfuser: Bringing User Interface Mock-ups to Life with Large Language Model Prompts
Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery (to appear)
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Large Language Models have enabled novices without machine learning (ML) experience to quickly prototype ML functionalities with prompt programming. This paper investigates incorporating prompt-based prototyping into designing functional user interface (UI) mock-ups. To understand how infusing LLM prompts into UI mock-ups might affect the prototyping process, we conduct a exploratory study with five designers, and find that this capability might significantly speed up creating functional prototypes, inform designers earlier on how their designs will integrate ML, and enable user studies with functional prototypes earlier. From these findings, we built PromptInfuser, a Figma plugin for authoring LLM-infused mock-ups. PromptInfuser introduces two novel LLM-interactions: input-output, which makes content interactive and dynamic, and frame-change, which directs users to different frames depending on their natural language input. From initial observations, we find that PromptInfuser has the potential to transform the design process by tightly integrating UI and AI prototyping in a single interface.
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