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December 9, 2024 | 5 minute read

Four Algoverse teams cited by researchers at Mount Sinai, NIH, Microsoft, Oxford, MIT, Princeton, and University of Washington.

Prompting paperDiversity paperQAP paperBias paper

We're thrilled to share that four of our student research papers have been cited by leading institutions and researchers in their papers on AI!

AAVENUE was cited by Microsoft, Oxford, and the University of Washington in “One Language, Many Gaps: Evaluating Dialect Fairness and Robustness of Large Language Models in Reasoning Tasks”. Their work highlights the importance of fairness and inclusivity in language models.

DiversityMedQA was cited by NIH in “Ensuring Safety and Trust: Analyzing the Risks of Large Language Models in Medicine”. Their work highlights the importance of ensuring reliability in AI medical applications.

Question-Analysis Prompting was cited by Mount Sinai in “A Strategy for Cost-Effective Large Language Model Use at Health System-Scale”, which explores strategies to balance the cost of AI in healthcare.

From Bias to Balance: Detecting Facial Expression Recognition Biases in Large Multimodal Foundation Models was cited by “GPT-4o Reads the Mind in the Eyes”, which explores GPT-4o's ability to interpret mental states from facial expressions.

These citations demonstrate the impact that young students can have on shaping the future of AI and its applications. We’re incredibly proud of them and the impact of their research.