Single-cell RNA sequencing (scRNA-seq) enables transcriptomic profiling at single-cell resolution, but accurate identification of cell subpopulations remains challenging because of the high dimensionality, sparsity, and dropout effects of scRNA-seq data. Existing deep learning-based clustering methods have shown promis...
Yuanyuan Dang, Wenqiang Liu, Hao Li et al.· Computational biology and ch...· 0 citations
Mixed SFT, a single supervised fine-tuning stage that jointly trains on no-CoT and long-CoT data, achieves a clearly higher post-RLVR performance ceiling than next-chunk reasoning RL while requiring over 60 times less training compute.
Yin-Hao Tang, You-Qing Fang, Ya-Nan Sun et al.· 1 citation
SciExplore is introduced, a benchmark designed to evaluate scientific information-seeking and reasoning capabilities of LLMs and agents, revealing substantial performance gaps with performance degrading sharply as task complexity increases and extremely low accuracy on the most challenging structured synthesis tasks.
Yinhao Tang, Youqing Fang, Yanan Sun et al.· Annual Meeting of the Associ...· 1 citation
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