Yiwei Lyu

Orcid: 0000-0002-3882-4246

Affiliations:
  • University of Michigan - Ann Arbor, MI, USA
  • Carnegie Mellon University, Language Technologies Institute, Machine Learning Department, Pittsburgh, PA, USA (2017 - 2022)


According to our database1, Yiwei Lyu authored at least 24 papers between 2019 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Towards Scalable Language-Image Pre-training for 3D Medical Imaging.
Trans. Mach. Learn. Res., 2026

2025
Learning complete and explainable visual representations from itemized text supervision.
CoRR, December, 2025

Health system learning achieves generalist neuroimaging models.
CoRR, November, 2025

Learning neuroimaging models from health system-scale data.
CoRR, September, 2025

Intelligent Histology for Tumor Neurosurgery.
CoRR, July, 2025

Step-Calibrated Diffusion for Biomedical Optical Image Restoration.
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024
A self-supervised framework for learning whole slide representations.
CoRR, 2024

Code Models are Zero-shot Precondition Reasoners.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Super-resolution of biomedical volumes with 2D supervision.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
High-Modality Multimodal Transformer: Quantifying Modality & Interaction Heterogeneity for High-Modality Representation Learning.
Trans. Mach. Learn. Res., 2023

MultiZoo and MultiBench: A Standardized Toolkit for Multimodal Deep Learning.
J. Mach. Learn. Res., 2023

MultiZoo & MultiBench: A Standardized Toolkit for Multimodal Deep Learning.
CoRR, 2023

Fine-grained Text Style Transfer with Diffusion-Based Language Models.
Proceedings of the 8th Workshop on Representation Learning for NLP, 2023

MultiViz: Towards Visualizing and Understanding Multimodal Models.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

TOD-Flow: Modeling the Structure of Task-Oriented Dialogues.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

MultiViz: Towards User-Centric Visualizations and Interpretations of Multimodal Models.
Proceedings of the Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

Nano: Nested Human-in-the-Loop Reward Learning for Few-shot Language Model Control.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
MultiViz: An Analysis Benchmark for Visualizing and Understanding Multimodal Models.
CoRR, 2022

HighMMT: Towards Modality and Task Generalization for High-Modality Representation Learning.
CoRR, 2022

DIME: Fine-grained Interpretations of Multimodal Models via Disentangled Local Explanations.
Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

2021
MultiBench: Multiscale Benchmarks for Multimodal Representation Learning.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

2019
The State and Future of Genetic Improvement.
ACM SIGSOFT Softw. Eng. Notes, 2019

Leveraging program invariants to promote population diversity in search-based automatic program repair.
Proceedings of the 6th International Workshop on Genetic Improvement, 2019


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