Publications (16)
Virtual Cells: From Conceptual Frameworks to Biomedical Applications
Saurabh Bhardwaj, Gaurav Kumar, Haochen Yang +5
The challenge of translating vast, multimodal biological data into predictive and mechanistic understanding of cellular function is a central theme in modern biology. Virtual cells…
Team Westwood Solution for MIDOG 2025 Challenge: An Ensemble-CNN-Based Approach For Mitosis Detection And Classification
Tengyou Xu, Haochen Yang, Xiang 'Anthony' Chen +2
This abstract presents our solution (Team Westwood) for mitosis detection and atypical mitosis classification in the MItosis DOmain Generalization (MIDOG) 2025 challenge. For mitos…
Optimal Transport for LLM Reward Modeling from Noisy Preference
Licheng Pan, Haochen Yang, Haoxuan Li +8
Reward models are fundamental to Reinforcement Learning from Human Feedback (RLHF), yet real-world datasets are inevitably corrupted by noisy preference. Conventional training obje…
Calibrating and Improving Graph Contrastive Learning
Kaili Ma, Haochen Yang, Han Yang +2
Graph contrastive learning algorithms have demonstrated remarkable success in various applications such as node classification, link prediction, and graph clustering. However, in u…
Reducing Belief Deviation in Reinforcement Learning for Active Reasoning
Deyu Zou, Yongqiang Chen, Jianxiang Wang +5
Active reasoning requires large language model (LLM) agents to interact with external sources and strategically gather information to solve problems in multiple turns. Central to t…
Can Machines Imitate Humans? Integrative Turing-like tests for Language and Vision Demonstrate a Narrowing Gap
Mengmi Zhang, Elisa Pavarino, Xiao Liu +20
As AI becomes increasingly embedded in daily life, ascertaining whether an agent is human is critical. We systematically benchmark AI's ability to imitate humans in three language…
Stealthy Multi-Task Adversarial Attacks
Jiacheng Guo, Tianyun Zhang, Lei Li +3
Deep neural networks are highly vulnerable to adversarial perturbations, raising serious safety concerns in the real-world systems. While prior work mainly explores single-task att…
Evaluating LLM Robustness Under Domain-Specific Prompt Perturbations in Public Health Applications
Chuqing Zhao, Haochen Yang
Large language models (LLMs) are increasingly applied in public health applications, yet their robustness to non-clinical user inputs remains underexplored. We propose a domain spe…
DarkDriving: A Real-World Day and Night Aligned Dataset for Autonomous Driving in the Dark Environment
Wuqi Wang, Haochen Yang, Baolu Li +7
The low-light conditions are challenging to the vision-centric perception systems for autonomous driving in the dark environment. In this paper, we propose a new benchmark dataset…
Topological shape transform for thymus structures
Haochen Yang, Vadim Lebovici, Andreas Tarcevski +6
The Euler characteristic transform (ECT) is an emerging and powerful framework within topological data analysis for quantifying the geometry of shape. The applicability of ECT has…
Unsupervised Multi-agent and Single-agent Perception from Cooperative Views
Haochen Yang, Baolu Li, Lei Li +5
The LiDAR-based multi-agent and single-agent perception has shown promising performance in environmental understanding for robots and automated vehicles. However, there is no exist…
Sample-Efficient Reinforcement Learning from Human Feedback via Information-Directed Sampling
Han Qi, Haochen Yang, Qiaosheng Zhang +1
We study the problem of reinforcement learning from human feedback (RLHF), a critical problem in training large language models, from a theoretical perspective. Our main contributi…
OptSkills: Learning Generalizable Optimization Skills from Problem Archetypes via Cluster-Based Distillation
Haochen Yang, Ke Zhao, Mengyuan Ma +3
Leveraging Large Language Models (LLMs) to automatically formulate and solve optimization problems from natural language has emerged as an efficient paradigm for automated optimiza…
Model-based Pre-clinical Trials for Medical Devices Using Statistical Model Checking
Haochen Yang, Jicheng Gu, Zhihao Jiang
Clinical trials are considered as the golden standard for medical device validation. However, many sacrifices have to be made during the design and conduction of the trials due to…
From Mind to Machine: The Rise of Manus AI as a Fully Autonomous Digital Agent
Minjie Shen, Yanshu Li, Lulu Chen +4
Manus AI is a general-purpose AI agent introduced in early 2025, marking a significant advancement in autonomous artificial intelligence. Developed by the Chinese startup Monica.im…
CATP: Cross-Attention Token Pruning for Accuracy Preserved Multimodal Model Inference
Ruqi Liao, Chuqing Zhao, Jin Li +4
In response to the rising interest in large multimodal models, we introduce Cross-Attention Token Pruning (CATP), a precision-focused token pruning method. Our approach leverages c…