3 citations · 6 across the 10 of their papers we have counts for
12 papers
VINCENT: Validated Interaction Network for Cross-drug Explanation of Therapeutics
Fan-Sheng Chuang, Xuchen Li, Yujing Bian +1
Drug synergy prediction estimates whether two drugs produce a stronger joint effect than expected from their individual activities. For drug combination discovery, a single synergy…
Vision Language Model Helps Private Information De-Identification in Vision Data
Tiejin Chen, Pingzhi Li, Kaixiong Zhou +2
Visual Language Models (VLMs) have gained significant popularity due to their remarkable ability. While various methods exist to enhance privacy in text-based applications, privacy…
Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges
Tiejin Chen, Pingzhi Li, Kaixiong Zhou +2
Privacy risks in text-only Large Language Models (LLMs) are well studied, particularly their tendency to memorize and leak sensitive information. However, Multi-modal Large Languag…
PRIME: Prototype-Driven Multimodal Pretraining for Cancer Prognosis with Missing Modalities
Kai Yu, Shuang Zhou, Yiran Song +9
Multimodal self-supervised pretraining offers a promising route to cancer prognosis by integrating histopathology whole-slide images, gene expression, and pathology reports, yet mo…
PPBoost: Progressive Prompt Boosting for Text-Driven Medical Image Segmentation
Xuchen Li, Hengrui Gu, Mohan Zhang +6
Text-prompted foundation models for medical image segmentation offer an intuitive way to delineate anatomical structures from natural language queries, but their predictions often…
Layer-Level Self-Exposure and Patch: Affirmative Token Mitigation for Jailbreak Attack Defense
Yang Ouyang, Hengrui Gu, Shuhang Lin +6
As large language models (LLMs) are increasingly deployed in diverse applications, including chatbot assistants and code generation, aligning their behavior with safety and ethical…
Continually Evolved Multimodal Foundation Models for Cancer Prognosis
Jie Peng, Shuang Zhou, Longwei Yang +7
Cancer prognosis is a critical task that involves predicting patient outcomes and survival rates. To enhance prediction accuracy, previous studies have integrated diverse data moda…
The Efficiency vs. Accuracy Trade-off: Optimizing RAG-Enhanced LLM Recommender Systems Using Multi-Head Early Exit
Huixue Zhou, Hengrui Gu, Xi Liu +15
The deployment of Large Language Models (LLMs) in recommender systems for predicting Click-Through Rates (CTR) necessitates a delicate balance between computational efficiency and…
Integrating Social Determinants of Health into Knowledge Graphs: Evaluating Prediction Bias and Fairness in Healthcare
Tianqi Shang, Weiqing He, Tianlong Chen +4
Social determinants of health (SDoH) play a crucial role in patient health outcomes, yet their integration into biomedical knowledge graphs remains underexplored. This study addres…
Cross-Lingual Multi-Hop Knowledge Editing
Aditi Khandelwal, Harman Singh, Hengrui Gu +2
Large language models are often expected to constantly adapt to new sources of knowledge and knowledge editing techniques aim to efficiently patch the outdated model knowledge, wit…
Benchmark on Drug Target Interaction Modeling from a Drug Structure Perspective
Xinnan Zhang, Jialin Wu, Junyi Xie +2
The prediction modeling of drug-target interactions is crucial to drug discovery and design, which has seen rapid advancements owing to deep learning technologies. Recently develop…
Privacy-preserving Fine-tuning of Large Language Models through Flatness
Tiejin Chen, Longchao Da, Huixue Zhou +4
The privacy concerns associated with the use of Large Language Models (LLMs) have grown recently with the development of LLMs such as ChatGPT. Differential Privacy (DP) techniques…