4 papers
Shapley Context Pruning: A Cooperative Game Perspective for Context Reranking and Pruning
Yanqiao Chen, Dongsheng Hou, Yuhan Rui +2
Context reranking and pruning have become essential for improving the efficiency of modern Retrieval-Augmented Generation (RAG) systems, yet an interpretable and unified framework…
FairMedQA: Benchmarking Bias in Large Language Models for Medical Question Answering
Ying Xiao, Jie Huang, Ruijuan He +6
Large language models (LLMs) are approaching expert-level performance in medical question answering (QA), demonstrating strong potential to improve public healthcare. However, unde…
Fairness Is Not Just Ethical: Performance Trade-Off via Data Correlation Tuning to Mitigate Bias in ML Software
Ying Xiao, Shangwen Wang, Sicen Liu +4
Traditional software fairness research typically emphasizes ethical and social imperatives, neglecting that fairness fundamentally represents a core software quality issue arising…
Inference performance evaluation for LLMs on edge devices with a novel benchmarking framework and metric
Hao Chen, Cong Tian, Zixuan He +3
With the significant success achieved by large language models (LLMs) like LLaMA, edge computing-based LLM inference services for mobile and PC are in high demand for data privacy.…