Nicholas Pellegrino

According to our database, Nicholas Pellegrino authored at least 14 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Pre-train to Gain: Robust Learning Without Clean Labels.

David Szczecina, Nicholas Pellegrino, Paul W. Fieguth

CoRR, November, 2025

Effects of Initialization Biases on Deep Neural Network Training Dynamics.

Nicholas Pellegrino, David Szczecina, Paul W. Fieguth

CoRR, November, 2025

Hard Samples, Bad Labels: Robust Loss Functions That Know When to Back Off.

Nicholas Pellegrino, David Szczecina, Paul W. Fieguth

CoRR, November, 2025

Hyperbolic Multimodal Representation Learning for Biological Taxonomies.

ZeMing Gong, Chuanqi Tang, Xiaoliang Huo, Nicholas Pellegrino, Austin T. Wang, Graham W. Taylor, Angel X. Chang, Scott C. Lowe, Joakim Bruslund Haurum

CoRR, August, 2025

Evaluating clinical AI summaries with large language models as judges.

Emma Croxford, Yanjun Gao, Elliot First, Nicholas Pellegrino, Miranda Schnier, John R. Caskey, Madeline Oguss, Graham Wills, Guanhua Chen, Dmitriy Dligach, Matthew M. Churpek, Anoop M. Mayampurath, Frank J. Liao, Cherodeep Goswami, Karen K. Wong, Brian W. Patterson, Majid Afshar

npj Digit. Medicine, 2025

Optimizing the efficiency and effectiveness of data quality assurance in a multicenter clinical dataset.

Anne Fu, Trong Shen, Surain B. Roberts, Weihan Liu, Shruthi Vaidyanathan, Kayley-Jasmin Marchena-Romero, Yuen Yu Phyllis Lam, Kieran Shah, Denise Y. F. Mak, Stephen Chin, Seth J. Stern, Radha Koppula, Lisa F. Joyce, Nicholas Pellegrino, Nancy Harris, Vivian Ng, Siddhartha Srivastava, Nathaniel Manikan, Amelia Wilkinson, Jenny Gastmeier, Jason C. Kwan, Hapiloe Byaruhanga, Linia Shaji, Siji George, Stephanie Handsor, Reshma Anna Roy, Chong Sung Kim, Selam Mequanint, Fahad Razak, Amol A. Verma

J. Am. Medical Informatics Assoc., 2025

Development and validation of the provider documentation summarization quality instrument for large language models.

Emma Croxford, Yanjun Gao, Nicholas Pellegrino, Karen K. Wong, Graham Wills, Elliot First, Miranda Schnier, Kyle Burton, Cris G. Ebby, Jillian Gorskic, Matthew Kalscheur, Samy Khalil, Marie Pisani, Tyler Rubeor, Peter D. Stetson, Frank J. Liao, Cherodeep Goswami, Brian W. Patterson, Majid Afshar

J. Am. Medical Informatics Assoc., 2025

2024

Evaluation of Large Language Models for Summarization Tasks in the Medical Domain: A Narrative Review.

Emma Croxford, Yanjun Gao, Nicholas Pellegrino, Karen K. Wong, Graham Wills, Elliot First, Frank J. Liao, Cherodeep Goswami, Brian W. Patterson, Majid Afshar

CoRR, 2024

Particle-Filtering-based Latent Diffusion for Inverse Problems.

Amir Nazemi, Mohammad Hadi Sepanj, Nicholas Pellegrino, Chris Czarnecki, Paul W. Fieguth

CoRR, 2024

BIOSCAN-5M: A Multimodal Dataset for Insect Biodiversity.

Zahra Gharaee, Scott C. Lowe, ZeMing Gong, Pablo Millan Arias, Nicholas Pellegrino, Austin T. Wang, Joakim Bruslund Haurum, Iuliia Zarubiieva, Lila Kari, Dirk Steinke, Graham W. Taylor, Paul W. Fieguth, Angel X. Chang

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

K-Means for noise-insensitive multi-dimensional feature learning.

Nicholas Pellegrino, Paul W. Fieguth, Parsin Haji Reza

Pattern Recognit. Lett., 2023

A Step Towards Worldwide Biodiversity Assessment: The BIOSCAN-1M Insect Dataset.

Zahra Gharaee, ZeMing Gong, Nicholas Pellegrino, Iuliia Zarubiieva, Joakim Bruslund Haurum, Scott C. Lowe, Jaclyn T. A. McKeown, Chris C. Y. Ho, Joschka McLeod, Yi-Yun C. Wei, Jireh Agda, Sujeevan Ratnasingham, Dirk Steinke, Angel X. Chang, Graham W. Taylor, Paul W. Fieguth

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Machine Learning Challenges of Biological Factors in Insect Image Data.

Nicholas Pellegrino, Zahra Gharaee, Paul W. Fieguth

CoRR, 2022

Normalized K-Means for Noise-Insensitive Multi-Dimensional Feature Learning.

Nicholas Pellegrino, Paul W. Fieguth, Parsin Haji Reza

CoRR, 2022