247 citations · 762 across the 30 of their papers we have counts for
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3 papers · 1 filter
cs.AI2022★ 7 cited
SATformer: Transformer-Based UNSAT Core Learning
Zhengyuan Shi, Min Li, Yi Liu +5
This paper introduces SATformer, a novel Transformer-based approach for the Boolean Satisfiability (SAT) problem. Rather than solving the problem directly, SATformer approaches the…
cs.AI2022★ 3 cited
DeepSAT: An EDA-Driven Learning Framework for SAT
Min Li, Zhengyuan Shi, Qiuxia Lai +3
We present DeepSAT, a novel end-to-end learning framework for the Boolean satisfiability (SAT) problem. Unlike existing solutions trained on random SAT instances with relatively we…
cs.AI2022★ 186 cited
Are Transformers Effective for Time Series Forecasting?
Ailing Zeng, Muxi Chen, Lei Zhang +1
Recently, there has been a surge of Transformer-based solutions for the long-term time series forecasting (LTSF) task. Despite the growing performance over the past few years, we q…