3 citations · 5 across the 7 of their papers we have counts for
7 papers
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…
You Only Debias Once: Towards Flexible Accuracy-Fairness Trade-offs at Inference Time
Xiaotian Han, Tianlong Chen, Kaixiong Zhou +3
Deep neural networks are prone to various bias issues, jeopardizing their applications for high-stake decision-making. Existing fairness methods typically offer a fixed accuracy-fa…
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…
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…
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expected to constantly adapt to new sources of knowledge and knowledge editing techniques aim to efficiently patch the outdated model knowledge, wit…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…