# xid32/NAACL\_2025\_TWM

<https://repo.masters-masters.com/en/repos/xid32/NAACL_2025_TWM>

[Home](https://repo.masters-masters.com/en) › [xid32](https://repo.masters-masters.com/en/owners/xid32) › [NAACL\_2025\_TWM](https://repo.masters-masters.com/en/repos/xid32/NAACL_2025_TWM)

xid32/NAACL\_2025\_TWM has 317 stars on GitHub. Its RepoMasters card: Alpha tier. We introduce temporal working memory (TWM), which aims to enhance the temporal…

| Field | Value |
| --- | --- |
| Owner | [xid32](https://repo.masters-masters.com/en/owners/xid32) |
| Stars | 317 |
| Forks | 30 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | None |
| Created | 2025 |
| Topics | multimodal-foundation-model, multimodal-large-language-models, audio-visual-learning, question-answering, video-captioning, video-text-retrieval, working-memory |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [xid32/NAACL\_2025\_TWM](https://github.com/xid32/NAACL_2025_TWM) |

## Repository

We introduce temporal working memory (TWM), which aims to enhance the temporal modeling capabilities of Multimodal foundation models (MFMs). This plug-and-play module can be easily integrated into existing MFMs. With our TWM, nine state-of-the-art models exhibit significant performance improvements…

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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