Yujia Bao

According to our database, Yujia Bao authored at least 16 papers between 2017 and 2024.

Collaborative distances:

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

2024

From Isolated Conversations to Hierarchical Schemas: Dynamic Tree Memory Representation for LLMs.

Alireza Rezazadeh, Zichao Li, Wei Wei, Yujia Bao

CoRR, 2024

LLM Unlearning via Loss Adjustment with Only Forget Data.

Yaxuan Wang, Jiaheng Wei, Chris Yuhao Liu, Jinlong Pang, Quan Liu, Ankit Parag Shah, Yujia Bao, Yang Liu, Wei Wei

CoRR, 2024

Improving Data Efficiency via Curating LLM-Driven Rating Systems.

Jinlong Pang, Jiaheng Wei, Ankit Parag Shah, Zhaowei Zhu, Yaxuan Wang, Chen Qian, Yang Liu, Yujia Bao, Wei Wei

CoRR, 2024

Harnessing Business and Media Insights with Large Language Models.

Yujia Bao, Ankit Parag Shah, Neeru Narang, Jonathan Rivers, Rajeev Maksey, Lan Guan, Louise N. Barrere, Shelley Evenson, Rahul Basole, Connie Miao, Ankit Mehta, Fabien Boulay, Su Min Park, Natalie E. Pearson, Eldhose Joy, Tiger He, Sumiran Thakur, Koustav Ghosal, Josh On, Phoebe Morrison, Tim Major, Eva Siqi Wang, Gina Escobar, Jiaheng Wei, Tharindu Cyril Weerasooriya, Queena Song, Daria Lashkevich, Clare Chen, Gyuhak Kim, Dengpan Yin, Don Hejna, Mo Nomeli, Wei Wei

CoRR, 2024

Sample, estimate, aggregate: A recipe for causal discovery foundation models.

Menghua Wu, Yujia Bao, Regina Barzilay, Tommi S. Jaakkola

CoRR, 2024

Channel Vision Transformers: An Image Is Worth 1 x 16 x 16 Words.

Yujia Bao, Srinivasan Sivanandan, Theofanis Karaletsos

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Channel Vision Transformers: An Image Is Worth C x 16 x 16 Words.

Yujia Bao, Srinivasan Sivanandan, Theofanis Karaletsos

CoRR, 2023

Contextual Vision Transformers for Robust Representation Learning.

Yujia Bao, Theofanis Karaletsos

CoRR, 2023

2022

Efficient and Robust Algorithms for Practical Machine Learning

Yujia Bao

PhD thesis, 2022

Learning to Split for Automatic Bias Detection.

Yujia Bao, Regina Barzilay

CoRR, 2022

Learning Stable Classifiers by Transferring Unstable Features.

Yujia Bao, Shiyu Chang, Regina Barzilay

Proceedings of the International Conference on Machine Learning, 2022

2021

Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers.

Yujia Bao, Shiyu Chang, Regina Barzilay

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Few-shot Text Classification with Distributional Signatures.

Yujia Bao, Menghua Wu, Shiyu Chang, Regina Barzilay

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Using Machine Learning and Natural Language Processing to Review and Classify the Medical Literature on Cancer Susceptibility Genes.

Yujia Bao, Zhengyi Deng, Yan Wang, Heeyoon Kim, Victor Diego Armengol, Francisco Acevedo, Nofal Ouardaoui, Cathy Wang, Giovanni Parmigiani, Regina Barzilay, Danielle Braun, Kevin S. Hughes

CoRR, 2019

2018

Deriving Machine Attention from Human Rationales.

Yujia Bao, Shiyu Chang, Mo Yu, Regina Barzilay

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

2017

Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data.

Yujia Bao, Zhaobin Kuang, Peggy L. Peissig, David Page, Rebecca Willett

Proceedings of the Machine Learning for Health Care Conference, 2017