Plug-and-Play: An Efficient Post-training Pruning Method for Large Language Models
No confident code implementation found for this paper. 5 possible matches can be shown below.
No confident code implementation found for this paper. 5 possible matches can be shown below.
No confident code match yet
We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 5 weaker matches are hidden by default — verify before relying on them.
No code implementations found yet.
Know of an implementation? Let us know in the comments below!
Train Once and Explain Everywhere: Pre-training Interpretable Graph Neural Networks
Scaling Laws for Pre-training Agents and World Models
Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules
PQ-SAM: Post-training Quantization for Segment Anything Model
POCA: Post-training Quantization with Temporal Alignment for Codec Avatars
On Pre-training Language Model for Antibody
@article{zhang2026plugandplay,
title = {Plug-and-Play: An Efficient Post-training Pruning Method for Large Language Models},
author = {Yingtao Zhang and Haoli Bai and Haokun Lin and Jialin Zhao and Lu Hou and C. Cannistraci},
year = {2026},
url = {https://api.semanticscholar.org/CorpusID:36e0b957b1a64bcc26bf8038e06e83122aec5a2a},
journal = {ICLR 2024 2024}
}Shows whether official code is linked for this paper.
[](https://codeofpaper.com/paper/36e0b957b1a64bcc26bf8038e06e83122aec5a2a)