ASAC (wip)
Implementation of Attention Schema-based Attention Control (ASAC), A Cognitive-Inspired Approach for Attention Management in Transformers
Citations
@misc{saxena2025attentionschemabasedattentioncontrol,
title = {Attention Schema-based Attention Control (ASAC): A Cognitive-Inspired Approach for Attention Management in Transformers},
author = {Krati Saxena and Federico Jurado Ruiz and Guido Manzi and Dianbo Liu and Alex Lamb},
year = {2025},
eprint = {2509.16058},
archivePrefix = {arXiv},
primaryClass = {cs.AI},
url = {https://arxiv.org/abs/2509.16058},
}
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Metadata
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Release files for ASAC-pytorch 0.0.20
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Source distribution (sdist)
| File | Size | Uploaded | |
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| asac_pytorch-0.0.20.tar.gz | 9.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| asac_pytorch-0.0.20-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 18.1 kB
Release files / asac_pytorch-0.0.20.tar.gz
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Release files / asac_pytorch-0.0.20-py3-none-any.whl
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| Size | 8.6 kB |
| Tags | Python 3 |
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