2 papers
cs.LG2026
HEAPr: Hessian-based Efficient Atomic Expert Pruning in Output Space
Ke Li, Zheng Yang, Zhongbin Zhou +3
Mixture-of-Experts (MoE) architectures in large language models (LLMs) deliver exceptional performance and reduced inference costs compared to dense LLMs. However, their large para…
cs.CV2025
HieraEdgeNet: A Multi-Scale Edge-Enhanced Framework for Automated Pollen Recognition
Yuchong Long, Wen Sun, Ningxiao Sun +3
Automated pollen recognition is vital to paleoclimatology, biodiversity monitoring, and public health, yet conventional methods are hampered by inefficiency and subjectivity. Exist…