2 research outputs found

    VLSlice: Interactive Vision-and-Language Slice Discovery

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    Recent work in vision-and-language demonstrates that large-scale pretraining can learn generalizable models that are efficiently transferable to downstream tasks. While this may improve dataset-scale aggregate metrics, analyzing performance around hand-crafted subgroups targeting specific bias dimensions reveals systemic undesirable behaviors. However, this subgroup analysis is frequently stalled by annotation efforts, which require extensive time and resources to collect the necessary data. Prior art attempts to automatically discover subgroups to circumvent these constraints but typically leverages model behavior on existing task-specific annotations and rapidly degrades on more complex inputs beyond "tabular" data, none of which study vision-and-language models. This paper presents VLSlice, an interactive system enabling user-guided discovery of coherent representation-level subgroups with consistent visiolinguistic behavior, denoted as vision-and-language slices, from unlabeled image sets. We show that VLSlice enables users to quickly generate diverse high-coherency slices in a user study (n=22) and release the tool publicly.Comment: Conference paper at ICCV 2023. 17 pages, 11 figures. https://ericslyman.com/vlslice

    Perfusion System for Modification of Luminal Contents of Human Intestinal Organoids and Realtime Imaging Analysis of Microbial Populations

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    Intestinal organoids are 3D cell structures that replicate some aspects of organ function and are organized with a polarized epithelium facing a central lumen. To enable more applications, new technologies are needed to access the luminal cavity and apical cell surface of organoids. We developed a perfusion system utilizing a double-barrel glass capillary with a pressure-based pump to access and modify the luminal contents of a human intestinal organoid for extended periods of time while applying cyclic cellular strain. Cyclic injection and withdrawal of fluorescent FITC-Dextran coupled with real-time measurement of fluorescence intensity showed discrete changes of intensity correlating with perfusion cycles. The perfusion system was also used to modify the lumen of organoids injected with GFP-expressing E. coli. Due to the low concentration and fluorescence of the E. coli, a novel imaging analysis method utilizing bacteria enumeration and image flattening was developed to monitor E. coli within the organoid. Collectively, this work shows that a double-barrel perfusion system provides constant luminal access and allows regulation of luminal contents and luminal mixing
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