In a highly globalized world, it is important for multi-modal language models to correctly recognize visuals in mixed-cultural settings. This paper examines the robustness of MLLMs to mixed cultures by constructing MixCuBe, a cross-cultural awareness benchmark of images and evaluating SOTA MLLMs on it.
The following are a few of demonstrable projects that I have implemented. If interested in more of my projects, please check out my Github.
A classic arcade style 2D shooting game wherein the player spaceship shoots at the enemies and bosses while avoiding their attacks.
Dynamic Brain Connectome Learning [Poster]
A set of graph machine learning architectures for learning temporal and spatial patterns of brain activation from fMRI images. Two downstream tasks are implemented: (1) brain activation prediction duration language tasks (link prediction) and (2) performance prediction from neural patterns (graph regression)
Advanced Passage Retrieval [Poster]
A NLP research into passage retrieval, the task of extracting top-k pertinent passages from a dataset as the output given a query as the input. We use the BM25 model as a benchmark to explore retrieval models that can achieve better accuracy specifically on the SQuAD1.1 dataset.
Myanmar (Burmese) 🇲🇲 Language Grapheme to Phoneme Converter for automatic speech recognition (ASR) and text-to-speech (TTS)
