Abstracts: NeurIPS 2024 with Pranjal Chitale
PRANJAL CHITALE: Hi, Gretchen. Thanks for having me.
HUIZINGA: So, Pranjal, give us an overview of this paper. In a couple sentences, what problem are you trying to solve, and why should people care about it?
CHITALE: So we are witnessing some exciting times as LLMs are rapidly evolving as tools for countless use cases. While most of these LLMs were initially leveraged for natural language processing tasks, they are now expanded across languages and modalities. However, a major gap lies in the availability of multimodal data for non-English languages. Therefore, most multimodal models might not have coverage for non-English languages altogether or might just heavily rely on translations of the associated text in English-centric datasets so as to support multiple languages. The drawback of this approach is that