ZQ
Zhiqiang Que
cs.LGcs.ARhep-exphysics.ins-detcs.AIastro-ph.IMcs.PFcs.SYeess.SY
On Valency
published · living versionsW_cq5armqu·v1 · currentpublished
LEAF: LUT-aware Efficient Attention on FPGAs
with Arianna Cox, Chang Sun, Lauri Laatu, Benedikt Maier +5
1 version
Preprints & journals
24 papers in the corpus · 2021–2026LEAF: LUT-aware Efficient Attention on FPGAs2610.27078v1 · Arianna Cox, Chang Sun, Lauri Laatu et al.2026 · 0 citationsarXivon Valency
LocalTrain: Integer-Only Local Learning for Energy-Efficient CNN Training on Edge FPGAs2610.17099v1 · Shiqi Ding, Xuanyu Liang, Xinyang Liu et al.2026 · 0 citationsarXiv
Alkaid: A Compiler Framework for Ultra-Low-Latency Kernels on Hardware2610.04808v1 · Chang Sun, Zhiqiang Que, Dimitrios Danopoulos et al.2026 · 0 citationsarXiv
HeteroReason: Heterogeneous FPGA-GPU Acceleration for Disaggregated Speculative Reasoning2609.28717v1 · Zehuan Zhang, Quan Deng, Zibo Ren et al.2026 · 0 citationsarXiv
FQTree: Fine-grained Quantization and Hardware Generation of Boosted Decision Trees2608.12140v1 · Zhiqiang Que, Chang Sun, Haiyang Wang et al.2026 · 0 citationsarXiv
SPEAR: A System for Post-Quantization Error-Adaptive Recovery Enabling Efficient Low-Bit LLM Serving2606.11244v1 · Hongyuan Liu, Yawei Li, Zhiqiang Que et al.2026 · 0 citationsarXiv
FFR: Forward-Forward Learning for Regression2606.03927v2 · Xinyang Liu, Xuanyu Liang, Shiqi Ding et al.2026 · 0 citationsarXiv
HGQ-LUT: Fast LUT-Aware Training and Efficient Architectures for DNN Inference2604.22293v1 · Chang Sun, Zhiqiang Que, Bakhtiar Zadeh et al.2026 · 0 citationsarXiv
JetFormer: A Scalable and Efficient Transformer for Jet Tagging from Offline Analysis to FPGA Triggers2601.17215v1 · Ruoqing Zheng, Chang Sun, Qibin Liu et al.2026 · 0 citationsarXiv
hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware2512.01463v1 · Jan-Frederik Schulte, Benjamin Ramhorst, Chang Sun et al.2025 · 10 citationsarXiv
Enhancing Trustworthiness with Mixed Precision: Benchmarks, Opportunities, and Challenges2511.22483v1 · Guanxi Lu, Hao Mark Chen, Zhiqiang Que et al.2025 · 0 citationsarXiv
Sub-microsecond Transformers for Jet Tagging on FPGAs2510.24784v1 · Lauri Laatu, Chang Sun, Arianna Cox et al.2025 · 0 citationsarXiv
JEDI-linear: Fast and Efficient Graph Neural Networks for Jet Tagging on FPGAs2508.15468v2 · Zhiqiang Que, Chang Sun, Sudarshan Paramesvaran et al.2025 · 2 citations2025 International Conference on Field Programmable Technology (ICFPT), Shanghai, China, 2025, pp. 171-179
da4ml: Distributed Arithmetic for Real-time Neural Networks on FPGAs2507.04535v2 · Chang Sun, Zhiqiang Que, Vladimir Loncar et al.2025 · 7 citationsACM Trans. Reconfig. Technol. Syst., Vol. 19, No. 1, Article 13. (March 2026)
Building Machine Learning Challenges for Anomaly Detection in Science2503.02112v2 · Elizabeth G. Campolongo, Yuan-Tang Chou, Ekaterina Govorkova et al.2025 · 0 citationsarXiv
MetaML-Pro: Cross-Stage Design Flow Automation for Efficient Deep Learning Acceleration2502.05850v3 · Zhiqiang Que, Jose G. F. Coutinho, Ce Guo et al.2025 · 4 citationsarXiv
Ultrafast jet classification on FPGAs for the HL-LHC2402.01876v2 · Patrick Odagiu, Zhiqiang Que, Javier Duarte et al.2024 · 10 citationsarXiv
When Monte-Carlo Dropout Meets Multi-Exit: Optimizing Bayesian Neural Networks on FPGA2308.06849v1 · Hongxiang Fan, Hao Chen, Liam Castelli et al.2023 · 6 citationsarXiv
High-Performance Acceleration of 2-D and 3-D CNNs on FPGAs Using Static Block Floating Point.34644253 · Fan, Hongxiang, Liu, Shuanglong, Que, Zhiqiang et al.2023 · 21 citationsIEEE transactions on neural networks and learning systems. 2023;34(8):4473-4487
MetaML: Automating Customizable Cross-Stage Design-Flow for Deep Learning Acceleration2306.08746v1 · Zhiqiang Que, Shuo Liu, Markus Rognlien et al.2023 · 6 citationsarXiv
LL-GNN: Low Latency Graph Neural Networks on FPGAs for High Energy Physics2209.14065v5 · Zhiqiang Que, Hongxiang Fan, Marcus Loo et al.2022 · 23 citationsarXiv
Algorithm and Hardware Co-design for Reconfigurable CNN Accelerator2111.12787v1 · Hongxiang Fan, Martin Ferianc, Zhiqiang Que et al.2021 · 16 citationsarXiv
Accelerating Recurrent Neural Networks for Gravitational Wave Experiments2106.14089v1 · Zhiqiang Que, Erwei Wang, Umar Marikar et al.2021 · 27 citationsarXiv
Optimizing Bayesian Recurrent Neural Networks on an FPGA-based Accelerator2106.06048v3 · Martin Ferianc, Zhiqiang Que, Hongxiang Fan et al.2021 · 12 citationsarXiv
Career total: 79 works. 24 are in this corpus.
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