2 papers
cs.CL2026
RiLM: Parameter-Efficient Language Modeling via Geodesic Decoding
Fang Li
Language models under one million parameters matter for edge deployment, domain adaptation, and reproducible research, yet a two-layer LSTM or Transformer at embedding width d = 12…
cs.LG2026
How Does Parameter Pruning Reshape DNN Representations? An Interaction-Driven Exploration
Fangbo Li, Junpeng Zhang, Qihan Ren +1
This study focuses on the scientific problem of understanding internal factors that govern the diverse performance degradation of deep neural networks (DNNs) when different paramet…