Beibin Li

According to our database, Beibin Li authored at least 34 papers between 2016 and 2025.

Collaborative distances:

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

2025

PathFinder: A Multi-Modal Multi-Agent System for Medical Diagnostic Decision-Making Applied to Histopathology.

Fatemeh Ghezloo, Mehmet Saygin Seyfioglu, Rustin Soraki, Wisdom Oluchi Ikezogwo, Beibin Li, Tejoram Vivekanandan, Joann G. Elmore, Ranjay Krishna, Linda G. Shapiro

CoRR, February, 2025

On the Emergence of Thinking in LLMs I: Searching for the Right Intuition.

Guanghao Ye, Khiem Duc Pham, Xinzhi Zhang, Sivakanth Gopi, Baolin Peng, Beibin Li, Janardhan Kulkarni, Huseyin A. Inan

CoRR, February, 2025

2024

Towards Foundation Models for Mixed Integer Linear Programming.

Sirui Li, Janardhan Kulkarni, Ishai Menache, Cathy Wu, Beibin Li

CoRR, 2024

Small Language Models for Application Interactions: A Case Study.

Beibin Li, Yi Zhang, Sébastien Bubeck, Jeevan Pathuri, Ishai Menache

CoRR, 2024

Computing in the Era of Large Generative Models: From Cloud-Native to AI-Native.

Yao Lu, Song Bian, Lequn Chen, Yongjun He, Yulong Hui, Matthew Lentz, Beibin Li, Fei Liu, Jialin Li, Qi Liu, Rui Liu, Xiaoxuan Liu, Lin Ma, Kexin Rong, Jianguo Wang, Yingjun Wu, Yongji Wu, Huanchen Zhang, Minjia Zhang, Qizhen Zhang, Tianyi Zhou, Danyang Zhuo

CoRR, 2024

Towards Safer Heuristics With XPlain.

Pantea Karimi, Solal Pirelli, Siva Kesava Reddy Kakarla, Ryan Beckett, Santiago Segarra, Beibin Li, Pooria Namyar, Behnaz Arzani

Proceedings of the 23rd ACM Workshop on Hot Topics in Networks, 2024

Reflect-RL: Two-Player Online RL Fine-Tuning for LMs.

Runlong Zhou, Simon S. Du, Beibin Li

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Stratification of Children with Autism Spectrum Disorder Through Fusion of Temporal Information in Eye-gaze Scan-Paths.

Adham Atyabi, Frederick Shic, Jiajun Jiang, Claire E. Foster, Erin Barney, Minah Kim, Beibin Li, Pamela Ventola, Chung-Hao Chen

ACM Trans. Knowl. Discov. Data, February, 2023

AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework.

Qingyun Wu, Gagan Bansal, Jieyu Zhang, Yiran Wu, Shaokun Zhang, Erkang Zhu, Beibin Li, Li Jiang, Xiaoyun Zhang, Chi Wang

CoRR, 2023

Large Language Models for Supply Chain Optimization.

Beibin Li, Konstantina Mellou, Bo Zhang, Jeevan Pathuri, Ishai Menache

CoRR, 2023

VSGD-Net: Virtual Staining Guided Melanocyte Detection on Histopathological Images.

Kechun Liu, Beibin Li, Wenjun Wu, Caitlin J. May, Oliver Chang, Stevan Knezevich, Lisa M. Reisch, Joann G. Elmore, Linda G. Shapiro

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Kerveros: Efficient and Scalable Cloud Admission Control.

Sultan Mahmud Sajal, Luke Marshall, Beibin Li, Shandan Zhou, Abhisek Pan, Konstantina Mellou, Deepak Narayanan, Timothy Zhu, David Dion, Thomas Moscibroda, Ishai Menache

Proceedings of the 17th USENIX Symposium on Operating Systems Design and Implementation, 2023

Virtual Machine Allocation with Lifetime Predictions.

Hugo Barbalho, Patricia Kovaleski, Beibin Li, Luke Marshall, Marco Molinaro, Abhisek Pan, Eli Cortez, Matheus Leao, Harsh Patwari, Zuzu Tang, Larissa Rozales Gonçalves, David Dion, Thomas Moscibroda, Ishai Menache

Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

Comparing Attention to Biological Motion in Autism across Age Groups Using Eye-Tracking.

Michal Hochhauser, Kelsey Jackson Dommer, Adham Atyabi, Beibin Li, Yeojin A. Ahn, Madeline Aubertine, Minah Kim, Sarah G. Corrigan, Kevin A. Pelphrey, Frederick Shic

Proceedings of the 2023 Symposium on Eye Tracking Research and Applications, 2023

Large-scale Investigations of AAC Usage Patterns: Trends, Autism, and Stacked Autoencoders.

Adham Atyabi, Laura Boccanfuso, James C. Snider, Minah Kim, Erin Barney, Amy Yeo-jin Ahn, Beibin Li, Kelsey Jackson Dommer, Frederick Shic

Proceedings of the 13th IEEE Annual Computing and Communication Workshop and Conference, 2023

2022

Low-Resource Neural Adaptation: A Unified Data Adaptation Framework for Neural Networks

Beibin Li

PhD thesis, 2022

Automated quantitative assessment of amorphous calcifications: Towards improved malignancy risk stratification.

Kalyani Marathe, Chrysostomos Marasinou, Beibin Li, Noor Nakhaei, Bo Li, Joann G. Elmore, Linda G. Shapiro, William Hsu

Comput. Biol. Medicine, 2022

Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts.

Beibin Li, Yao Lu, Srikanth Kandula

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

Calibration Error Prediction: Ensuring High-Quality Mobile Eye-Tracking.

Beibin Li, James C. Snider, Quan Wang, Sachin Mehta, Claire E. Foster, Erin Barney, Linda G. Shapiro, Pamela Ventola, Frederick Shic

Proceedings of the ETRA 2022: Symposium on Eye Tracking Research and Applications, Seattle, WA, USA, June 8, 2022

2021

Q-error Bounds of Random Uniform Sampling for Cardinality Estimation.

Beibin Li, Yao Lu, Chi Wang, Srikanth Kandula

CoRR, 2021

Learning Oculomotor Behaviors from Scanpath.

Beibin Li, Nicholas Nuechterlein, Erin Barney, Claire E. Foster, Minah Kim, Monique Mahony, Adham Atyabi, Li Feng, Quan Wang, Pamela Ventola, Linda G. Shapiro, Frederick Shic

Proceedings of the ICMI '21: International Conference on Multimodal Interaction, 2021

Learning Melanocytic Proliferation Segmentation in Histopathology Images From Imperfect Annotations.

Kechun Liu, Mojgan Mokhtari, Beibin Li, Shima Nofallah, Caitlin J. May, Oliver Chang, Stevan Knezevich, Joann G. Elmore, Linda G. Shapiro

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020

Pyglmnet: Python implementation of elastic-net regularized generalized linear models.

Mainak Jas, Titipat Achakulvisut, Aid Idrizovic, Daniel E. Acuna, Matthew Antalek, Vinícius Marques, Tommy Odland, Ravi Garg, Mayank Agrawal, Yu Umegaki, Peter Foley, Hugo Fernandes, Drew Harris, Beibin Li, Olivier Pieters, Scott Otterson, Giovanni De Toni, Chris C. Rodgers, Eva L. Dyer, Matti S. Hämäläinen, Konrad P. Körding, Pavan Ramkumar

J. Open Source Softw., 2020

Leveraging Unlabeled Data for Glioma Molecular Subtype and Survival Prediction.

Nicholas Nuechterlein, Beibin Li, Mehmet Saygin Seyfioglu, Sachin Mehta, Patrick J. Cimino, Linda G. Shapiro

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Classifying Breast Histopathology Images with a Ductal Instance-Oriented Pipeline.

Beibin Li, Ezgi Mercan, Sachin Mehta, Stevan Knezevich, Corey W. Arnold, Donald L. Weaver, Joann G. Elmore, Linda G. Shapiro

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Selection of Eye-Tracking Stimuli for Prediction by Sparsely Grouped Input Variables for Neural Networks: towards Biomarker Refinement for Autism.

Beibin Li, Erin Barney, Caitlin Hudac, Nicholas Nuechterlein, Pamela Ventola, Linda G. Shapiro, Frederick Shic

Proceedings of the ETRA '20: 2020 Symposium on Eye Tracking Research and Applications, 2020

2019

Sparsely Grouped Input Variables for Neural Networks.

Beibin Li, Nicholas Nuechterlein, Erin Barney, Caitlin Hudac, Pamela Ventola, Linda G. Shapiro, Frederick Shic

CoRR, 2019

A Facial Affect Analysis System for Autism Spectrum Disorder.

Beibin Li, Sachin Mehta, Deepali Aneja, Claire E. Foster, Pamela Ventola, Frederick Shic, Linda G. Shapiro

Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

2018

Social Influences on Executive Functioning in Autism: Design of a Mobile Gaming Platform.

Beibin Li, Adham Atyabi, Minah Kim, Erin Barney, Amy Yeo-jin Ahn, Yawen Luo, Madeline Aubertine, Sarah Corrigan, Tanya St. John, Quan Wang, Marilena Mademtzi, Mary Best, Frederick Shic

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 2018

2017

An exploratory analysis targeting diagnostic classification of AAC app usage patterns.

Adham Atyabi, Beibin Li, Amy Yeo-jin Ahn, Minah Kim, Erin Barney, Frederick Shic

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2016

A thermal emotion classifier for improved human-robot interaction.

Laura Boccanfuso, Quan Wang, Iolanda Leite, Beibin Li, Colette Torres, Lisa Chen, Nicole Salomons, Claire E. Foster, Erin Barney, Amy Yeo-jin Ahn, Brian Scassellati, Frederick Shic

Proceedings of the 25th IEEE International Symposium on Robot and Human Interactive Communication, 2016

Thermographic eye tracking.

Quan Wang, Laura Boccanfuso, Beibin Li, Amy Yeo-jin Ahn, Claire E. Foster, Margaret P. Orr, Brian Scassellati, Frederick Shic

Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications, 2016

Optimality of the distance dispersion fixation identification algorithm.

Beibin Li, Quan Wang, Laura Boccanfuso, Frederick Shic

Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications, 2016

Modified DBSCAN algorithm on oculomotor fixation identification.

Beibin Li, Quan Wang, Erin Barney, Logan Hart, Carla A. Wall, Katarzyna Chawarska, Irati Saez de Urabain, Timothy J. Smith, Frederick Shic

Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications, 2016