#pruning
4 papers · 1 filter
AtlasLC: Fast Codec-Ready Compression of Object-Centric 3D Gaussian Splatting
ByungHyun Kim, Jinwoo Jeon, Woontack Woo
AtlasLC is a source‑free, training‑free pipeline that quickly compresses object‑centric 3D Gaussian Splatting assets for XR, cutting preparation and compression time while preservi…
Gibbs randomness-compression proposition
M. Süzen, M Süzen
The paper proposes a theorem linking Gibbs entropy (a measure of randomness) to lossy model compression, showing that the entropy of remaining network weights correlates with learn…
Towards Efficient Convolutional Neural Network for Embedded Hardware via Multi-Dimensional Pruning
Hao Kong, Di Liu, Xiangzhong Luo +5
The paper introduces TECO, a framework that jointly prunes depth, width, and input resolution of convolutional neural networks to improve speed and resource usage on embedded devic…
OS-Pruner: Pruning Chains-of-Thought of Reasoning Models via Optimal Stopping
Mohammed Ehab, Aymane El Gadarri, Vivek F. Farias +2
The paper proposes OS-Pruner, a lightweight framework that treats chain-of-thought reasoning in large language models as an optimal stopping problem, allowing the model to stop gen…