GTAC applies a generative Transformer with irredundant encoding and self-evolutionary training to produce approximate circuits that cut delay by 30.9% and gate count by 50.5% versus baselines while using far less memory.
Alignment unlocks complemen- tarity: A framework for multiview circuit representation learning.arXiv preprint arXiv:2509.20968, 2025
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AR 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
GTAC: A Generative Transformer for Approximate Circuits
GTAC applies a generative Transformer with irredundant encoding and self-evolutionary training to produce approximate circuits that cut delay by 30.9% and gate count by 50.5% versus baselines while using far less memory.