Code for "Language Model Knowledge Distillation for Efficient Question Answering in Spanish" (ICLR 2024 Tiny Papers)
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Updated
Dec 5, 2023 - Python
Code for "Language Model Knowledge Distillation for Efficient Question Answering in Spanish" (ICLR 2024 Tiny Papers)
Denoising Diffusion Step-aware Models (ICLR2024)
[ECCV 2020 Oral] MutualNet: Adaptive ConvNet via Mutual Learning from Network Width and Resolution
Official Website for the Workshop on Advancing Neural Networks Training: Computational Efficiency, Scalability, and Resource Optimization (WANT@ICML 2024, WANT@NeurIPS 2023)
Recent Advances on Efficient Vision Transformers
[ICML'24 Oral] APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
This repository is for reproducing the results shown in the NNCodec ICML Workshop paper. Additionally, it includes a demo, prepared for the Neural Compression Workshop (NCW).
[ICML 2024] CrossGET: Cross-Guided Ensemble of Tokens for Accelerating Vision-Language Transformers.
Code repository of the paper "Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups" https://proceedings.mlr.press/v162/knigge22a.html
[ICLR 2022] "Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently", by Xiaohan Chen, Jason Zhang and Zhangyang Wang.
[Preprint] Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Pruning
Official PyTorch training code of Accelerating Deep Neural Networks via Semi-Structured Activation Sparsity (ICCV2023-RCV)
A generic code base for neural network pruning, especially for pruning at initialization.
[ICLR'23] Trainability Preserving Neural Pruning (PyTorch)
Official PyTorch implementation of "Meta-prediction Model for Distillation-Aware NAS on Unseen Datasets" (ICLR 2023 notable top 25%)
[CVPR 2024] Dynamic Adapter Meets Prompt Tuning: Parameter-Efficient Transfer Learning for Point Cloud Analysis
Official implementation of "EAGLES: Efficient Accelerated 3D Gaussians with Lightweight EncodingS"
[ICLR'24] "DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training" by Aochuan Chen*, Yimeng Zhang*, Jinghan Jia, James Diffenderfer, Jiancheng Liu, Konstantinos Parasyris, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu
[IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.
[NeurIPS 2019 Google MicroNet Challenge] MSUNet is an efficient model that won the 4th place in the Google MicroNet Challenge CIFAR-100 Track hosted at NeurIPS 2019 designed by Yu Zheng, Shen Yan, Mi Zhang
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