TrilinearCIM enables complete in-memory Transformer attention computation via DG-FeFET three-operand MAC without runtime NVM reprogramming, delivering up to 46.6% energy reduction and 20.4% latency improvement on BERT and ViT benchmarks at 37.3% area cost.
Tunnel and capacitive coupling optimization in FDSOI spin-qubit devices
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3representative citing papers
Presents a DFNG model for ferroelectric domain nucleation and growth under arbitrary voltage waveforms to enable predictive materials-to-circuit co-design.
Fast gate-based reflectometry readout of Pauli spin blockade and tunable interdot coupling demonstrated in industry-fabricated silicon double quantum dots.
citing papers explorer
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Trilinear Compute-in-Memory Architecture for Energy-Efficient Transformer Acceleration
TrilinearCIM enables complete in-memory Transformer attention computation via DG-FeFET three-operand MAC without runtime NVM reprogramming, delivering up to 46.6% energy reduction and 20.4% latency improvement on BERT and ViT benchmarks at 37.3% area cost.
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Ferroelectric dynamic-field-driven nucleation and growth model for predictive materials-to-circuit co-design
Presents a DFNG model for ferroelectric domain nucleation and growth under arbitrary voltage waveforms to enable predictive materials-to-circuit co-design.
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Fast readout for large scale spin-based qubits
Fast gate-based reflectometry readout of Pauli spin blockade and tunable interdot coupling demonstrated in industry-fabricated silicon double quantum dots.