Research at Algoverse
Learn about our mission, explore our acclaimed conference publications, and delve into past student research papers.
Our Commitment to Quality Research
Algoverse AI Research is dedicated to empowering students to create authentic and impactful AI research. Our distinctive emphasis on quality and process enables our students to produce exceptional research published at leading NLP conferences worldwide. We strive to push the boundaries of large language models (LLMs) on standard benchmarks while pioneering machine learning applications across diverse disciplines. This commitment to innovation and excellence sets us apart from other programs.
Our PhD mentors have extensive experience conducting cutting-edge research at top AI institutions and research labs around the globe. They are deeply invested in each student's project, providing essential mentorship in scoping research proposals, implementing code, and academic writing. Through this guidance, our students are uniquely equipped to produce high-quality research papers and successfully navigate the publication process at prestigious conferences. Past papers of our students have been cited by researchers at Microsoft, Oxford, and University of Washington.
Conference Publications
Translation Bias and Accuracy in Multilingual LLMs for Cross-Language Claim Verification
Accepted to Attribution @ NeurIPS 2024 in Vancouver, Canada
Authors: Aryan Singhal, Veronica Shao, Gary Sun, Ryan Ding
QIANets for Reduced Latency and Improved Inference Times in CNN Models
Accepted to Compression @ NeurIPS 2024 in Vancouver, Canada
Authors: Zhumazhan Balapanov, Edward Magongo, Vanessa Matvei, Olivia Holmberg
Semantic Self-Consistency: Enhancing Language Model Reasoning via Semantic Weighting
Accepted to MathAI @ NeurIPS 2024 in Vancouver, Canada
Authors: Tim Knappe, Ryan Li, Ayush Chauhan, Kaylee Chhua
Fine-Tuning Language Models for Ethical Ambiguity
Accepted to SoLaR @ NeurIPS 2024 in Vancouver, Canada
Authors: Pranav Senthilkumar, Visshwa Bala, Prisha Jain, Aneesa Maity
NusaMT-7B: Machine Translation for Low-Resource Indonesian Languages with LLMs
Accepted to SoLaR @ NeurIPS 2024 in Vancouver, Canada
Author: William Tan
Pragmatic Metacognitive Prompting Improves LLM Performance on Sarcasm Detection
Accepted to CHum 2025 @ COLING 2025 in Abu Dhabi, UAE
Authors: Joshua Lee, Wyatt Fong, Alexander Le, Sur Shah
Differentiation of Acute Disseminated Encephalomyelitis from Multiple Sclerosis Using a Novel Brain Lesion Segmentation and Classification Pipeline
Accepted to IEEE BHI 2024 in Houston, Texas, USA
Authors: Osama Radi, Aiden Huang, Kira Murukami
Medical Imaging Complexity and its Effects on GAN Performance
Accepted to GAISynMeD @ ACCV 2024 in Hanoi, Vietnam
Authors: William Cagas, Chan Ko, Blake Hsiao, Shryuk Grandhi, and Rishi Bhattacharya
DiversityMedQA: Assessing Demographic Biases in Medical Diagnosis using LLMs
Accepted to AIM-FM @ NeurIPS 2024 in Vancouver, Canada
Accepted to EMNLP Positive Impact Track 2024 in Miami, Florida
Authors: Rajat Rawat, Hudson McBride, Rajarshi Ghosh, Dhiyaan Nirmal, Jong Moon, Dhruv Alamuri
AAVENUE: Detecting LLM Biases on NLU Tasks in AAVE via a Novel Benchmark
Accepted to NeurIPS High School Track 2024 in Vancouver, Canada
Accepted to EMNLP Positive Impact Track 2024 in Miami, Florida
Authors: Abhay Gupta, Philip Meng, Ece Yurtseven
Improving LLM Abilities in Idiomatic Translation
Accepted to LoResLM 2025 @ COLING 2025 in Abu Dhabi, UAE
Authors: Sundesh Donthi, Maximilian Spencer, Om Patel, Joon Doh, Eid Rodan
Question-Analysis-Prompting Improves LLM Performance in Reasoning Tasks
Accepted to ACL SRW 2024 in Bangkok, Thailand
Author: Dharunish Yugeswardeenoo
Applied Machine Learning Research
Explore our applied machine learning research, driving innovation across diverse fields and solving real-world challenges.
Large Language Models Research
Delve into cutting-edge research on large language models, pushing the boundaries of natural language understanding and generation.
