papers

Publications (6)

cs.CL2026

Lowest Span Confidence: A Zero-Shot Metric for Efficient and Black-Box Hallucination Detection in LLMs

Yitong Qiao, Licheng Pan, Yu Mi +4

Hallucinations in Large Language Models (LLMs), i.e., the tendency to generate plausible but non-factual content, pose a significant challenge for their reliable deployment in high…

cs.CL2025

scAgent: Universal Single-Cell Annotation via a LLM Agent

Yuren Mao, Yu Mi, Peigen Liu +3

Cell type annotation is critical for understanding cellular heterogeneity. Based on single-cell RNA-seq data and deep learning models, good progress has been made in annotating a f…

cs.IR2026

LFRAG: Layout-oriented Fine-grained Retrieval-Augmented Generation on Multimodal Document Understanding

Yifan Zhu, Yu Mi, Yue Lu +2

Multimodal Retrieval-Augmented Generation (RAG) has emerged as an effective paradigm for enhancing Large Language Models (LLMs) with external knowledge. However, existing multimoda…

cs.LG2024

A Survey on LoRA of Large Language Models

Yuren Mao, Yuhang Ge, Yijiang Fan +4

Low-Rank Adaptation~(LoRA), which updates the dense neural network layers with pluggable low-rank matrices, is one of the best performed parameter efficient fine-tuning paradigms.…

cs.CL2024

FinSQL: Model-Agnostic LLMs-based Text-to-SQL Framework for Financial Analysis

Chao Zhang, Yuren Mao, Yijiang Fan +5

Text-to-SQL, which provides zero-code interface for operating relational databases, has gained much attention in financial analysis; because, financial professionals may not well-s…

cs.NI2025

Tree embedding based mapping system for low-latency mobile applications in multi-access networks

Yu Mi, Randeep Bhatia, Fang Hao +3

Low-latency applications like AR/VR and online gaming need fast, stable connections. New technologies such as V2X, LEO satellites, and 6G bring unique challenges in mobility manage…