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cs.CL2026
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…
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…