22 citations · 62 across the 28 of their papers we have counts for
29 papers
Learning complete and explainable visual representations from itemized text supervision
Yiwei Lyu, Chenhui Zhao, Soumyanil Banerjee +5
Training vision models with language supervision enables general and transferable representations. However, many visual domains, especially non-object-centric domains such as medic…
Health system learning achieves generalist neuroimaging models
Akhil Kondepudi, Akshay Rao, Chenhui Zhao +14
Frontier artificial intelligence (AI) models, such as OpenAI's GPT-5 and Meta's DINOv3, have advanced rapidly through training on internet-scale public data, yet such systems lack…
Learning neuroimaging models from health system-scale data
Yiwei Lyu, Samir Harake, Asadur Chowdury +18
Neuroimaging is a ubiquitous tool for evaluating patients with neurological diseases. The global demand for magnetic resonance imaging (MRI) studies has risen steadily, placing sig…
Intelligent Histology for Tumor Neurosurgery
Xinhai Hou, Akhil Kondepudi, Cheng Jiang +27
The importance of rapid and accurate histologic analysis of surgical tissue in the operating room has been recognized for over a century. Our standard-of-care intraoperative pathol…
Towards Scalable Language-Image Pre-training for 3D Medical Imaging
Chenhui Zhao, Yiwei Lyu, Asadur Chowdury +6
The scalability of current language-image pre-training for 3D medical imaging, such as CT and MRI, is constrained by the need for radiologists to manually curate raw clinical studi…
Super-resolution of biomedical volumes with 2D supervision
Cheng Jiang, Alexander Gedeon, Yiwei Lyu +7
Volumetric biomedical microscopy has the potential to increase the diagnostic information extracted from clinical tissue specimens and improve the diagnostic accuracy of both human…
Step-Calibrated Diffusion for Biomedical Optical Image Restoration
Yiwei Lyu, Sung Jik Cha, Cheng Jiang +7
High-quality, high-resolution medical imaging is essential for clinical care. Raman-based biomedical optical imaging uses non-ionizing infrared radiation to evaluate human tissues…
A self-supervised framework for learning whole slide representations
Xinhai Hou, Cheng Jiang, Akhil Kondepudi +4
Whole slide imaging is fundamental to biomedical microscopy and computational pathology. Previously, learning representations for gigapixel-sized whole slide images (WSIs) has reli…
TOD-Flow: Modeling the Structure of Task-Oriented Dialogues
Sungryull Sohn, Yiwei Lyu, Anthony Liu +4
Task-Oriented Dialogue (TOD) systems have become crucial components in interactive artificial intelligence applications. While recent advances have capitalized on pre-trained langu…
Code Models are Zero-shot Precondition Reasoners
Lajanugen Logeswaran, Sungryull Sohn, Yiwei Lyu +5
One of the fundamental skills required for an agent acting in an environment to complete tasks is the ability to understand what actions are plausible at any given point. This work…
MultiZoo & MultiBench: A Standardized Toolkit for Multimodal Deep Learning
Paul Pu Liang, Yiwei Lyu, Xiang Fan +4
Learning multimodal representations involves integrating information from multiple heterogeneous sources of data. In order to accelerate progress towards understudied modalities an…
Fine-grained Text Style Transfer with Diffusion-Based Language Models
Yiwei Lyu, Tiange Luo, Jiacheng Shi +2
Diffusion probabilistic models have shown great success in generating high-quality images controllably, and researchers have tried to utilize this controllability into text generat…
Risk-aware Safe Control for Decentralized Multi-agent Systems via Dynamic Responsibility Allocation
Yiwei Lyu, Wenhao Luo, John M. Dolan
Decentralized control schemes are increasingly favored in various domains that involve multi-agent systems due to the need for computational efficiency as well as general applicabi…
Active Probing and Influencing Human Behaviors Via Autonomous Agents
Shuangge Wang, Yiwei Lyu, John M. Dolan
Autonomous agents (robots) face tremendous challenges while interacting with heterogeneous human agents in close proximity. One of these challenges is that the autonomous agent doe…
Model-based Dynamic Shielding for Safe and Efficient Multi-Agent Reinforcement Learning
Wenli Xiao, Yiwei Lyu, John Dolan
Multi-Agent Reinforcement Learning (MARL) discovers policies that maximize reward but do not have safety guarantees during the learning and deployment phases. Although shielding wi…
Minimally Constrained Multi-Robot Coordination with Line-of-sight Connectivity Maintenance
Yupeng Yang, Yiwei Lyu, Wenhao Luo
In this paper, we consider a team of mobile robots executing simultaneously multiple behaviors by different subgroups, while maintaining global and subgroup line-of-sight (LOS) net…
Safe Reinforcement Learning with Probabilistic Control Barrier Functions for Ramp Merging
Soumith Udatha, Yiwei Lyu, John Dolan
Prior work has looked at applying reinforcement learning and imitation learning approaches to autonomous driving scenarios, but either the safety or the efficiency of the algorithm…
Nano: Nested Human-in-the-Loop Reward Learning for Few-shot Language Model Control
Xiang Fan, Yiwei Lyu, Paul Pu Liang +2
Pretrained language models have demonstrated extraordinary capabilities in language generation. However, real-world tasks often require controlling the distribution of generated te…
MultiViz: Towards Visualizing and Understanding Multimodal Models
Paul Pu Liang, Yiwei Lyu, Gunjan Chhablani +5
The promise of multimodal models for real-world applications has inspired research in visualizing and understanding their internal mechanics with the end goal of empowering stakeho…
Responsibility-associated Multi-agent Collision Avoidance with Social Preferences
Yiwei Lyu, Wenhao Luo, John M. Dolan
This paper introduces a novel social preference-aware decentralized safe control framework to address the responsibility allocation problem in multi-agent collision avoidance. Cons…
Provable Probabilistic Safety and Feasibility-Assured Control for Autonomous Vehicles using Exponential Control Barrier Functions
Spencer Van Koevering, Yiwei Lyu, Wenhao Luo +1
With the increasing need for safe control in the domain of autonomous driving, model-based safety-critical control approaches are widely used, especially Control Barrier Function (…
DIME: Fine-grained Interpretations of Multimodal Models via Disentangled Local Explanations
Yiwei Lyu, Paul Pu Liang, Zihao Deng +2
The ability for a human to understand an Artificial Intelligence (AI) model's decision-making process is critical in enabling stakeholders to visualize model behavior, perform mode…
High-Modality Multimodal Transformer: Quantifying Modality & Interaction Heterogeneity for High-Modality Representation Learning
Paul Pu Liang, Yiwei Lyu, Xiang Fan +6
Many real-world problems are inherently multimodal, from spoken language, gestures, and paralinguistics humans use to communicate, to force, proprioception, and visual sensors on r…
Adaptive Safe Merging Control for Heterogeneous Autonomous Vehicles using Parametric Control Barrier Functions
Yiwei Lyu, Wenhao Luo, John M. Dolan
With the increasing emphasis on the safe autonomy for robots, model-based safe control approaches such as Control Barrier Functions have been extensively studied to ensure guarante…