Yueqi Song

I am a fourth year undergraduate student at Carnegie Mellon University, where I am pursuing a dual degree in Computer Science and Statistics and Machine Learning, with a minor in Computational Finance. My expected graduation date is May, 2024. I am applying to PhD programs with starting time in Fall 2024.
I am broadly interested in NLP for social good. Previously I worked on multilingual NLP where we evaluated global progress of language technologies. Currently, I am working on a multimodal multicultural grounded reasoning project, where we aim to improve visio-linguistic models' explainability and generalizability across languages and cultures. We propose various pipelines to achieve this goal. In addition, I am also open to new directions.

I have been fortunate to work with an amazing set of researchers in the past. I am doing my senior honors thesis at Carnegie Mellon University where I am very grateful to be advised by Professor Graham Neubig. In addition to my time in research, I interned at Intuit as a software engineer in AI/ML team, and PreVeil as a software developer. For more details, please check my CV or hit me up on my email: yueqis@andrew.cmu.edu :)

GlobalBench: A Benchmark for Global Progress in Natural Language Processing
Yueqi Song, Catherine Cui, Simran Khanuja, Pengfei Liu, Fahim Faisal, Alissa Ostapenko, Genta Indra Winata, Alham Fikri Aji, Samuel Cahyawijaya, Yulia Tsvetkov, Antonios Anastasopoulos, Graham Neubig
EMNLP 2023
pdf| abstract Brief Summary: This work introduces GlobalBench, an ever-expanding collection that aims to dynamically track progress on all NLP datasets in all languages and tracks the estimated per-speaker utility and equity of technology across all languages, providing a multi-faceted view of how language technology is serving people from all language groups around the world.