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cs.CL2024
Steering Large Language Models to Evaluate and Amplify Creativity
Matthew Lyle Olson, Neale Ratzlaff, Musashi Hinck +2
Although capable of generating creative text, Large Language Models (LLMs) are poor judges of what constitutes "creativity". In this work, we show that we can leverage this knowled…
cs.CL2024
Why do LLaVA Vision-Language Models Reply to Images in English?
Musashi Hinck, Carolin Holtermann, Matthew Lyle Olson +6
We uncover a surprising multilingual bias occurring in a popular class of multimodal vision-language models (VLMs). Including an image in the query to a LLaVA-style VLM significant…
cs.CL2024
LLaVA-Gemma: Accelerating Multimodal Foundation Models with a Compact Language Model
Musashi Hinck, Matthew L. Olson, David Cobbley +2
We train a suite of multimodal foundation models (MMFM) using the popular LLaVA framework with the recently released Gemma family of large language models (LLMs). Of particular int…