HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark. - Chaojian Li; Zhongzhi Yu; Yonggan Fu; Yongan Zhang; Yang Zhao 013; Haoran You; Qixuan Yu 001; Yue Wang 036; Cong Hao; Yingyan Lin (ICLR, 2021)

Double-Win Quant: Aggressively Winning Robustness of Quantized Deep Neural Networks via Random Precision Training and Inference. - Yonggan Fu; Qixuan Yu 001; Meng Li 004; Vikas Chandra; Yingyan Lin (ICML, 2021)

2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency. - Yonggan Fu; Yang Zhao 013; Qixuan Yu 001; Chaojian Li; Yingyan Lin (MICRO, 2021)

Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks. - Yonggan Fu; Qixuan Yu 001; Yang Zhang 001; Shang Wu 003; Xu Ouyang; David D. Cox; Yingyan Lin (NeurIPS, 2021)

HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark. - Chaojian Li; Zhongzhi Yu; Yonggan Fu; Yongan Zhang; Yang Zhao 013; Haoran You; Qixuan Yu 001; Yue Wang 036; Yingyan Lin (CoRR, 2021)

A Lossless and Modeling Attack-Resistant Strong PUF with <4E-8 Bit Error Rate. - Yan He 002; Qixuan Yu 001; Kaiyuan Yang 001 (CICC, 2022)

Contrastive quant: quantization makes stronger contrastive learning. - Yonggan Fu; Qixuan Yu 001; Meng Li 004; Xu Ouyang; Vikas Chandra; Yingyan Lin (DAC, 2022)

Software-hardware codesign for efficient in-memory regular pattern matching. - Lingkun Kong; Qixuan Yu 001; Agnishom Chattopadhyay; Alexis Le Glaunec; Yi Huang; Konstantinos Mamouras; Kaiyuan Yang 001 (PLDI, 2022)