14 papers
Leveraging Metamemory Agent for Enhanced Data-Free Code Generation in Large Language Models
Shengsheng Zhou, Shuai Wang, Liang Ding +5
Large language models (LLMs) have shown strong performance in automated code generation, with few-shot prompting widely used for its simplicity and effectiveness. However, few-shot…
PREBA: Surgical Duration Prediction via PCA-Weighted Retrieval-Augmented LLMs and Bayesian Averaging Aggregation
Wanyin Wu, Kanxue Li, Baosheng Yu +4
Accurate prediction of surgical duration is pivotal for hospital resource management. Although recent supervised learning approaches-from machine learning (ML) to fine-tuned large…
Towards Reliable Medical LLMs: Benchmarking and Enhancing Confidence Estimation of Large Language Models in Medical Consultation
Zhiyao Ren, Yibing Zhan, Siyuan Liang +3
Large-scale language models (LLMs) often offer clinical judgments based on incomplete information, increasing the risk of misdiagnosis. Existing studies have primarily evaluated co…
Cross-Sample Augmented Test-Time Adaptation for Personalized Intraoperative Hypotension Prediction
Kanxue Li, Yibing Zhan, Hua Jin +3
Intraoperative hypotension (IOH) poses significant surgical risks, but accurate prediction remains challenging due to patient-specific variability. While test-time adaptation (TTA)…
Bi-Level Optimization for Self-Supervised AI-Generated Face Detection
Mian Zou, Nan Zhong, Baosheng Yu +2
AI-generated face detectors trained via supervised learning typically rely on synthesized images from specific generators, limiting their generalization to emerging generative tech…
ProGMLP: A Progressive Framework for GNN-to-MLP Knowledge Distillation with Efficient Trade-offs
Weigang Lu, Ziyu Guan, Wei Zhao +5
GNN-to-MLP (G2M) methods have emerged as a promising approach to accelerate Graph Neural Networks (GNNs) by distilling their knowledge into simpler Multi-Layer Perceptrons (MLPs).…