Xing, Eric P.

Theoretically principled trade-off between robustness and accuracy

Zhang, H., Yu, Y., Jiao, J., Xing, E. P., Ghaoui, L. E., & Jordan, M. I. (2019) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 1,560

Learning Robust Global Representations by Penalizing Local Predictive Power

Wang, H., Ge, S., Xing, E. P., & Lipton, Z. C. (2019) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 337

Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation

Li, C. Y., Liang, X., Hu, Z., & Xing, E. P. (2018) · arXiv

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 271

GET: a foundation model of transcription across human cell types

Fu, X., Mo, S., Buendia, A., Laurent, A., Shao, A., Alvares-Torres, M. D. M., Yu, T., Tan, J., Su, J., Sagatelian, R., et al. (2023) · Nature

Genomics and Chromatin DynamicsGene Regulatory Network Analysis

Cited by 130

Learning sparse nonparametric DAGs.

Zheng, X., Dan, C., Aragam, B., Ravikumar, P., & Xing, E. P. (2019) · arXiv

Bayesian Modeling and Causal InferenceStatistical Methods and Inference

Cited by 103

PathVQA: 30000+ Questions for Medical Visual Question Answering

He, X., Zhang, Y., Mou, L., Xing, E., & Xie, P. (2020) · arXiv

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 79

Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space

Chavan, A., Shen, Z., Liu, Z., Liu, Z., Cheng, K.-T., & Xing, E. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsMachine Learning and Data Classification

Cited by 72

Progressive Generation of Long Text with Pretrained Language Models

Tan, B., Yang, Z., Al-Shedivat, M., Xing, E., & Hu, Z. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingNatural Language Processing Techniques

Cited by 69

LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Zheng, L., Chiang, W.-L., Sheng, Y., Li, T., Zhuang, S., Wu, Z., Zhuang, Y., Li, Z., Lin, Z., Xing, E. P., et al. (2023) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 27

Efficient (Soft) Q-Learning for Text Generation with Limited Good Data

Guo, H., Tan, B., Liu, Z., Xing, E. P., & Hu, Z. (2021) · arXiv

Topic ModelingReinforcement Learning in Robotics

Cited by 20

RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning

Deng, M., Wang, J., Hsieh, C.-P., Wang, Y., Guo, H., Shu, T., Song, M., Xing, E. P., & Hu, Z. (2022) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 14

SlimPajama-DC: Understanding Data Combinations for LLM Training

Shen, Z., Tao, T., Ma, L., Neiswanger, W., Liu, Z., Wang, H., Tan, B., Hestness, J., Vassilieva, N., Soboleva, D., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 3

LLM360: Towards Fully Transparent Open-Source LLMs

Liu, Z., Qiao, A., Neiswanger, W., Wang, H., Tan, B., Tao, T., Li, J., Wang, Y., Sun, S., Pangarkar, O., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 3

Pandora: Towards General World Model with Natural Language Actions and Video States

Xiang, J., Liu, G., Gu, Y., Gao, Q., Ning, Y., Zha, Y., Feng, Z., Tao, T., Hao, S., Shi, Y., et al. (2024) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 1

MegaMath: Pushing the Limits of Open Math Corpora

Zhou, F., Wang, Z., Ranjan, N., Cheng, Z., Tang, L., He, G., Liu, Z., & Xing, E. P. (2025) · arXiv

Topic ModelingMathematics, Computing, and Information Processing

Cited by 0

Log-Linear Attention

Guo, H., Yang, S., Goel, T., Xing, E. P., Dao, T., & Kim, Y. (2025) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 0