118 citations · 128 across the 16 of their papers we have counts for
4 papers · 1 filter
Can We Predict Before Executing Machine Learning Agents?
Jingsheng Zheng, Jintian Zhang, Yujie Luo +5
Autonomous machine learning agents have revolutionized scientific discovery, yet they remain constrained by a Generate-Execute-Feedback paradigm. Previous approaches suffer from a…
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…
Large-Small Model Collaboration for Enhancing Edge-Deployed Small Models
Peigen Liu, Yijiang Fan, Zixuan Xu +3
Edge devices host domain-specific small language models (SLMs) with limited resources, while private clouds offer larger LLMs. We propose G-Boost, an adaptive edge-cloud framework…
FIT-RAG: Black-Box RAG with Factual Information and Token Reduction
Yuren Mao, Xuemei Dong, Wenyi Xu +3
Due to the extraordinarily large number of parameters, fine-tuning Large Language Models (LLMs) to update long-tail or out-of-date knowledge is impractical in lots of applications.…