A Unified Library for Parameter-Efficient and Modular Transfer Learning
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Updated
Nov 2, 2024 - Jupyter Notebook
A Unified Library for Parameter-Efficient and Modular Transfer Learning
A curated list of prompt-based paper in computer vision and vision-language learning.
[ICML2024 (Oral)] Official PyTorch implementation of DoRA: Weight-Decomposed Low-Rank Adaptation
A collection of parameter-efficient transfer learning papers focusing on computer vision and multimodal domains.
Research Trends in LLM-guided Multimodal Learning.
Collection of Tools and Papers related to Adapters / Parameter-Efficient Transfer Learning/ Fine-Tuning
[ICCV 2023 & AAAI 2023] Binary Adapters & FacT, [Tech report] Convpass
Official implementation for CVPR'23 paper "BlackVIP: Black-Box Visual Prompting for Robust Transfer Learning"
On Transferability of Prompt Tuning for Natural Language Processing
Official implementation of AAAI 2023 paper "Parameter-efficient Model Adaptation for Vision Transformers"
[ICLR 2024] This is the repository for the paper titled "DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning"
[NeurIPS2023] Parameter-efficient Tuning of Large-scale Multimodal Foundation Model
[ICML 2024] Official code for the paper "Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark ".
[CVPR2024] The code of "UniPT: Universal Parallel Tuning for Transfer Learning with Efficient Parameter and Memory"
Code for paper "UniPELT: A Unified Framework for Parameter-Efficient Language Model Tuning", ACL 2022
[arXiv] Cross-Modal Adapter for Text-Video Retrieval
ZhiJian: A Unifying and Rapidly Deployable Toolbox for Pre-trained Model Reuse
[CVPR 2023] VoP: Text-Video Co-operative Prompt Tuning for Cross-Modal Retrieval
[Preprint] AdaVAE: Exploring Adaptive GPT-2s in VAEs for Language Modeling PyTorch Implementation
[AAAI 2024] DGL: Dynamic Global-Local Prompt Tuning for Text-Video Retrieval.
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