3 papers
cs.LG2026
Self-Improving is Often Sudden: Enlightenment-style Finetuning for Large-Scale Models
Jing-Xiao Liao, Tianwei Zhang, Yu-Hao Jiang +3
The pursuit of autonomously self-improving models has attracted growing interest in the era of large-scale foundation models. Drawing inspiration from the concept of "enlightenment…
cs.CV2025
Compress Any Segment Anything Model (SAM)
Juntong Fan, Zhiwei Hao, Jianqiang Shen +4
Due to the excellent performance in yielding high-quality, zero-shot segmentation, Segment Anything Model (SAM) and its variants have been widely applied in diverse scenarios such…
cs.LG2025
NeuronSeek: On Stability and Expressivity of Task-driven Neurons
Hanyu Pei, Jing-Xiao Liao, Qibin Zhao +4
Drawing inspiration from our human brain that designs different neurons for different tasks, recent advances in deep learning have explored modifying a network's neurons to develop…