Algoverse students successfully showcased their research at the EMNLP (Conference on Empirical Methods in Natural Language Processing) Positive Impact Track 2024. EMNLP is one of the most prestigious conferences in NLP.
Group 1: Abhay Gupta and Philip Meng presented "Detecting LLM Biases on NLU Tasks in AAVE via a Novel Benchmark." Their research addressed equitable NLP and the importance of addressing biases in language models, particularly concerning African American Vernacular English (AAVE). Paper: https://www.arxiv.org/pdf/2408.14845
Group 2: Rajat Rawat, Hudson McBride, Rajarshi Ghosh, and Dhiyaan presented "DiversityMedQA: Assessing Demographic Biases in Medical Diagnosis using Large Language Models." Their findings contributed to discussions on fairness in AI applications, particularly in medical settings. Paper: https://arxiv.org/pdf/2409.01497
The students networked with Ph.D. and industrial researchers, gaining exposure to other projects in the field.
