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2020 – today
- 2024
[c20]Runlong Zhou, Simon S. Du, Beibin Li:
Reflect-RL: Two-Player Online RL Fine-Tuning for LMs. ACL (1) 2024: 995-1015- [i10]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:
Computing in the Era of Large Generative Models: From Cloud-Native to AI-Native. CoRR abs/2401.12230 (2024) - [i9]Runlong Zhou, Simon S. Du, Beibin Li:
Reflect-RL: Two-Player Online RL Fine-Tuning for LMs. CoRR abs/2402.12621 (2024) - [i8]Beibin Li, Yi Zhang, Sébastien Bubeck, Jeevan Pathuri, Ishai Menache:
Small Language Models for Application Interactions: A Case Study. CoRR abs/2405.20347 (2024) - 2023
- [j3]Adham Atyabi, Frederick Shic, Jiajun Jiang, Claire E. Foster, Erin Barney, Minah Kim, Beibin Li, Pamela Ventola, Chung-Hao Chen:
Stratification of Children with Autism Spectrum Disorder Through Fusion of Temporal Information in Eye-gaze Scan-Paths. ACM Trans. Knowl. Discov. Data 17(2): 25:1-25:20 (2023) - [c19]Adham Atyabi, Laura Boccanfuso, James C. Snider, Minah Kim, Erin Barney, Amy Yeo-jin Ahn, Beibin Li, Kelsey Jackson Dommer, Frederick Shic:
Large-scale Investigations of AAC Usage Patterns: Trends, Autism, and Stacked Autoencoders. CCWC 2023: 851-859 - [c18]Michal Hochhauser, Kelsey Jackson Dommer, Adham Atyabi, Beibin Li, Yeojin A. Ahn, Madeline Aubertine, Minah Kim, Sarah G. Corrigan, Kevin A. Pelphrey, Frederick Shic:
Comparing Attention to Biological Motion in Autism across Age Groups Using Eye-Tracking. ETRA 2023: 36:1-36:3 - [c17]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:
Virtual Machine Allocation with Lifetime Predictions. MLSys 2023 - [c16]Sultan Mahmud Sajal, Luke Marshall, Beibin Li, Shandan Zhou, Abhisek Pan, Konstantina Mellou, Deepak Narayanan, Timothy Zhu, David Dion, Thomas Moscibroda, Ishai Menache:
Kerveros: Efficient and Scalable Cloud Admission Control. OSDI 2023: 227-245 - [c15]Kechun Liu, Beibin Li, Wenjun Wu, Caitlin J. May, Oliver Chang, Stevan Knezevich, Lisa M. Reisch, Joann G. Elmore, Linda G. Shapiro:
VSGD-Net: Virtual Staining Guided Melanocyte Detection on Histopathological Images. WACV 2023: 1918-1927 - [i7]Beibin Li, Konstantina Mellou, Bo Zhang, Jeevan Pathuri, Ishai Menache:
Large Language Models for Supply Chain Optimization. CoRR abs/2307.03875 (2023) - [i6]Qingyun Wu, Gagan Bansal, Jieyu Zhang, Yiran Wu, Shaokun Zhang, Erkang Zhu, Beibin Li, Li Jiang, Xiaoyun Zhang, Chi Wang:
AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework. CoRR abs/2308.08155 (2023) - 2022
- [b1]Beibin Li:
Low-Resource Neural Adaptation: A Unified Data Adaptation Framework for Neural Networks. University of Washington, USA, 2022 - [j2]Kalyani Marathe, Chrysostomos Marasinou, Beibin Li, Noor Nakhaei, Bo Li, Joann G. Elmore, Linda G. Shapiro, William Hsu:
Automated quantitative assessment of amorphous calcifications: Towards improved malignancy risk stratification. Comput. Biol. Medicine 146: 105504 (2022) - [c14]Beibin Li, James C. Snider, Quan Wang, Sachin Mehta, Claire E. Foster, Erin Barney, Linda G. Shapiro, Pamela Ventola, Frederick Shic:
Calibration Error Prediction: Ensuring High-Quality Mobile Eye-Tracking. ETRA 2022: 17:1-17:7 - [c13]Beibin Li, Yao Lu, Srikanth Kandula:
Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts. SIGMOD Conference 2022: 1920-1933 - 2021
- [c12]Kechun Liu, Mojgan Mokhtari, Beibin Li, Shima Nofallah, Caitlin J. May, Oliver Chang, Stevan Knezevich, Joann G. Elmore, Linda G. Shapiro:
Learning Melanocytic Proliferation Segmentation in Histopathology Images From Imperfect Annotations. CVPR Workshops 2021: 3766-3775 - [c11]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:
Learning Oculomotor Behaviors from Scanpath. ICMI 2021: 407-415 - [i5]Beibin Li, Yao Lu, Chi Wang, Srikanth Kandula:
Q-error Bounds of Random Uniform Sampling for Cardinality Estimation. CoRR abs/2108.02715 (2021) - [i4]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:
Learning Oculomotor Behaviors from Scanpath. CoRR abs/2108.05025 (2021) - 2020
- [j1]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:
Pyglmnet: Python implementation of elastic-net regularized generalized linear models. J. Open Source Softw. 5(47): 1959 (2020) - [c10]Beibin Li, Erin Barney, Caitlin Hudac, Nicholas Nuechterlein, Pamela Ventola, Linda G. Shapiro, Frederick Shic:
Selection of Eye-Tracking Stimuli for Prediction by Sparsely Grouped Input Variables for Neural Networks: towards Biomarker Refinement for Autism. ETRA 2020: 21:1-21:8 - [c9]Nicholas Nuechterlein, Beibin Li, Mehmet Saygin Seyfioglu, Sachin Mehta, Patrick J. Cimino, Linda G. Shapiro:
Leveraging Unlabeled Data for Glioma Molecular Subtype and Survival Prediction. ICPR 2020: 7149-7156 - [c8]Beibin Li, Ezgi Mercan, Sachin Mehta, Stevan Knezevich, Corey W. Arnold, Donald L. Weaver, Joann G. Elmore, Linda G. Shapiro:
Classifying Breast Histopathology Images with a Ductal Instance-Oriented Pipeline. ICPR 2020: 8727-8734 - [i3]Beibin Li, Ezgi Mercan, Sachin Mehta, Stevan Knezevich, Corey W. Arnold, Donald L. Weaver, Joann G. Elmore, Linda G. Shapiro:
Classifying Breast Histopathology Images with a Ductal Instance-Oriented Pipeline. CoRR abs/2012.06136 (2020)
2010 – 2019
- 2019
- [c7]Beibin Li, Sachin Mehta, Deepali Aneja, Claire E. Foster, Pamela Ventola, Frederick Shic, Linda G. Shapiro:
A Facial Affect Analysis System for Autism Spectrum Disorder. ICIP 2019: 4549-4553 - [i2]Beibin Li, Sachin Mehta, Deepali Aneja, Claire E. Foster, Pamela Ventola, Frederick Shic, Linda G. Shapiro:
A Facial Affect Analysis System for Autism Spectrum Disorder. CoRR abs/1904.03616 (2019) - [i1]Beibin Li, Nicholas Nuechterlein, Erin Barney, Caitlin Hudac, Pamela Ventola, Linda G. Shapiro, Frederick Shic:
Sparsely Grouped Input Variables for Neural Networks. CoRR abs/1911.13068 (2019) - 2018
- [c6]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:
Social Influences on Executive Functioning in Autism: Design of a Mobile Gaming Platform. CHI 2018: 443 - 2017
- [c5]Adham Atyabi, Beibin Li, Amy Yeo-jin Ahn, Minah Kim, Erin Barney, Frederick Shic:
An exploratory analysis targeting diagnostic classification of AAC app usage patterns. IJCNN 2017: 1633-1640 - 2016
- [c4]Quan Wang, Laura Boccanfuso, Beibin Li, Amy Yeo-jin Ahn, Claire E. Foster, Margaret P. Orr, Brian Scassellati, Frederick Shic:
Thermographic eye tracking. ETRA 2016: 307-310 - [c3]Beibin Li, Quan Wang, Erin Barney, Logan Hart, Carla A. Wall, Katarzyna Chawarska, Irati Saez de Urabain, Timothy J. Smith, Frederick Shic:
Modified DBSCAN algorithm on oculomotor fixation identification. ETRA 2016: 337-338 - [c2]Beibin Li, Quan Wang, Laura Boccanfuso, Frederick Shic:
Optimality of the distance dispersion fixation identification algorithm. ETRA 2016: 339-340 - [c1]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:
A thermal emotion classifier for improved human-robot interaction. RO-MAN 2016: 718-723
Coauthor Index
aka: Frederick Shic
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