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The Paper List of Large Multi-Modality Model (Perception, Generation, Unification), Parameter-Efficient Finetuning, Vision-Language Pretraining, Conventional Image-Text Matching for Preliminary Insight.
| Date | Stars |
|---|---|
| 2026-07-24 | 446 |
| 2026-07-25 | 446 |
| 2026-07-28 | 446 |
| 2026-07-30 | 446 |
| 2026-08-06 | 446 |
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Awesome_Matching_Pretraining_Transfering
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The awesome tutorial of **Large Multi-Modality Model**, **Parameter-Efficient Finetuning**, **Vision-Language Pretraining**, **Conventional Image-Text Matching** will be constantly updated for Preliminary Insight !
## ``Logupdate ``
【2025.09.26】 **Due to time constraints, I will update 300+ LMMM section further soon.**
【2024.03.09】 A new section named ***[Large Multi-Modality Model]*** has been added.
【2023.05.25】 A new section named ***[Parameter-Efficient Finetuning]*** has been added.
【2021.07.10】 A new section named ***[Vision-Language Pretraining]*** has been added.
【2020.11.01】 A new section named ***[Conventional Image-Text Matching]*** has been added.
## ``Catalogue ``
* [Large Multi-Modality Model](./large_mmm.md)
* [Large Language Model](./large_mmm.md/#large-language-model)
* [Large Vision Model](./large_mmm.md/#large-vision-model)
* [Large MMM for Perception](./large_mmm.md/#large-mmm-for-perception)
* [Large MMM for Generation](./large_mmm.md/#large-mmm-for-generation)
* [Large MMM for Unification](./large_mmm.md/#large-mmm-for-unification)
* [Large MMM for Manipulation](./large_mmm.md/#large-mmm-for-manipulation)
* [Large Model Distillation](./large_mmm.md/#large-modal-distillation)
* [Related Survey](./large_mmm.md/#related-survey)
* [Related Benchmark](./large_mmm.md/#related-benchmark)
* [Parameter-Efficient Finetuning](./transfer_learning.md)
* [Prompt Tuning](./transfer_learning.md/#prompt-tuning)
* [Adapter Tuning](./transfer_learning.md/#adapter-tuning)
* [Partially Tuning](./transfer_learning.md/#partially-tuning)
* [Side Tuning](./transfer_learning.md/#side-tuning)
* [Unified Tuning](./transfer_learning.md/#unified-tuning)
* [Posted in](./transfer_learning.md/#posted-in)
* [Vision-Language Pretraining](./pretrained_model.md)
* [Image-Language Pretraining](./pretrained_model.md/#image-language-pretraining)
* [Video-Language Pretraining](./pretrained_model.md/#video-language-pretraining)
* [Image-Language Datasets](./pretrained_model.md/#image-language-datasets)
* [Video-Language Datasets](./pretrained_model.md/#video-language-datasets)
* [Conventional Image-Text Matching](./conventional_method.md)
* [Generic-Feature Extraction](./conventional_method.md/#generic-feature-extraction)
* [Cross-Modal Interaction](./conventional_method.md/#cross-modal-interaction)
* [Similarity Measurement](./conventional_method.md/#similarity-measurement)
* [Uncertainty Learning](./conventional_method.md/#uncertainty-learning)
* [Noisy Correspondence](./conventional_method.md/#noisy-correspondence)
* [Commonsense Learning](./conventional_method.md/#commonsense-learning)
* [Adversarial Learning](./conventional_method.md/#adversarial-learning)
* [Loss Function](./conventional_method.md/#loss-function)
* [Un-/Semi-Supervised](./conventional_method.md/#un-supervised-or-semi-supervised)
* [Zero-/Fewer-Shot](./conventional_method.md/#zero-shot-or-fewer-shot)
* [Continual Learning](./conventional_method.md/#continual-learning)
* [Identification Learning](./conventional_method.md/#identification-learning)
* [Video-Text Learning](https://github.com/danieljf24/awesome-video-text-retrieval)
* [Scene-Text Learning](./conventional_method.md/#scene-text-learning)
* [Related Works](./conventional_method.md/#related-works)
* [Posted in](./conventional_method.md/#posted-in)
* [Peformance](./performance.md)
* [Flickr8K](./performance.md/#performance-of-flickr8k)
* [Flickr30K](./performance.md/#performance-of-flickr30k)
* [MSCOCO1K](./performance.md/#performance-of-mscoco1k)
* [MSCOCO5K](./performance.md/#performance-of-mscoco5k)
* [RSTPReid](./performance.md/#performance-of-rstpreid)
* [CUHK-PEDES](./performance.md/#performance-of-cuhk-pedes)
* [ICFGExcerpt of 4,591 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:ab9745f0c54151c0, topic:awesome-list, topic:tutorial, readme:tutorial
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