Boxun Xu

University of California, Santa Barbara.

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4164 Harold Frank Hall

Santa Barbara, CA 93106

I am a final-year Ph.D. student in Electrical and Computer Engineering at UC Santa Barbara, advised by Prof.Peng Li (IEEE Fellow). My research interests focus on the intersection of machine learning and computer architecture. Specifically, brain-inspired machine learning, efficient ML systems, and multimodal content generation. I received consecutive William J. McCalla Best Paper Award nominations at ICCAD 2024 and ICCAD 2025. I also completed research internships at Meta in 2024 and at Meta Superintelligence Labs(MSL) in 2025.

Since 2025, my research has focused on efficient and scalable multimodal generative models and world models.

I received my M.S. in Electrical and Computer Engineering from the University of Michigan, Ann Arbor, advised by Prof. David Blaauw (IEEE Fellow) and Prof. Dennis Sylvester (IEEE Fellow), and my B.S. in Electronic Engineering from the University of Electronic Science and Technology of China.

Research focus Efficient Generative Modeling HW/Algorithm Co-design & EDA Multimodal & World Models

news

Feb 15, 2026 One paper is accepted by CVPR 2026 Findings!
Nov 15, 2025 Two papers are accepted by AAAI 2026!
Oct 26, 2025 Our work has been nominated for the William J. McCalla Best Paper Award at ICCAD 2025, for the second consecutive year!
Jun 30, 2025 One paper is accepted by ICCAD 2025!
May 23, 2025 One paper is accepted by ITC 2025!
Apr 29, 2025 One paper is accepted by ASAP 2025!
Mar 21, 2025 One paper is accepted by International Symposium on Computer Architecture (ISCA’25)! See you in Tokyo!
Jan 18, 2025 Our work has been accepted by IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems(TCAD) as a long paper!
Jan 03, 2025 This summer, I will join Meta Logo, working on Efficient Movie Generation in Seattle!
Oct 26, 2024 Our Work “Spiking Transformer Accelerators in 3D Integration” is nominated as William J. McCalla Best Paper Award at ICCAD’24!
Jul 01, 2024 Two papers are accepted by ICCAD 2024!
Jun 24, 2024 I started my summer internship at Meta Logo, working on Knowledge Distillation of Multi-modal Foundation Models.
May 25, 2024 One paper is accepted by JSSC.

selected publications

Efficient Generative Modeling

  1. AAAI’26
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    ★ AMS-KV: Adaptive KV Caching in Multi-Scale Visual Autoregressive Transformers
    Boxun Xu, Yu Wang, Zihu Wang, and Peng Li
    In AAAI Conference on Artificial Intelligence (main track)(Acceptance Rate: 17.6%) , 2026
    First efficient KV-caching design tailored for multi-scale visual AR transformers.
  2. Preprint
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    ★ Sparse Forcing: Native Trainable Sparse Attention for Real-time Autoregressive Video Generation
    Boxun Xu, Yuming Du, Zichang Liu, Siyu Yang, Ziyang Jiang, Siqi Yan, Rajasi Saha, Albert Pumarola, Wenchen Wang, and Peng Li
    In under internal review, 2025
    First native trainable sparse-attention framework enabling real-time autoregressive video generation.
  3. ICCV’25
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    VAR-Q: Tuning-free Quantized KV Caching for Visual Autoregressive Models
    Boxun Xu*, Jiaji Lu*, Zihu Wang, Yu Wang, Zirui Liu, and Peng Li
    In IEEE/CVF International Conference on Computer Vision (ICCV) Workshop on Binary and Extreme Quantization for Computer Vision, 2025
  4. CVPR’26
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    VEGAS: Mitigating Hallucinations in Large Vision-Language Models via Vision-Encoder Attention Guided Adaptive Steering
    Zihu Wang, Boxun Xu, and  others
    In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Findings, 2026

Hardware/Algorithm Co-design and EDA

  1. ISCA’25
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    ★ Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning
    Boxun Xu, Yuxuan Yin, Vikram Iyer, and Peng Li
    In International Symposium on Computer Architecture (ISCA)(Acceptance Rate: 22.2%) , 2025
    First SW/HW co-design framework for neuromorphic transformers.
  2. ICCAD’25
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    🏆 Nominated as William J. McCalla Best Paper Award in 2025
    ★ 3D Acceleration for Mixture-of-Experts and Multi-Head Attention Spiking Transformers with Dynamic Head Pruning
    Boxun Xu, Junyoung Hwang, Pruek Vanna-iampikul, Yuxuan Yin, Sung Kyu Lim, and Peng Li
    In ACM/IEEE International Conference on Computer-Aided Design (ICCAD)(Acceptance Rate: 24.7%) , 2025
    First 3D-integrated accelerator for Mixture-of-Experts spiking transformers with dynamic head pruning.
  3. ICCAD’24
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    🏆 Nominated as William J. McCalla Best Paper Award in 2024
    ★ Spiking Transformer Hardware Accelerators in 3D Integration
    Boxun Xu, Junyoung Hwang, Pruek Vanna-iampikul, Sung-Kyu Lim, and Peng Li
    In ACM/IEEE International Conference on Computer-Aided Design (ICCAD)(Acceptance Rate: 24%) , 2024
    First 3D-integrated hardware accelerator for spiking transformers.
  4. TCAD’25
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    SpikeX: Exploring Accelerator Architecture and Network-Hardware Co-Optimization for Sparse Spiking Neural Networks
    Boxun Xu, Richard Boone, and Peng Li
    In IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems(TCAD), 2025
  5. ASAP’25
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    Trimming Down Large Spiking Vision Transformers via Heterogeneous Quantization Search
    Boxun Xu*, Yufei Song*, and Peng Li
    In IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP), 2025
  6. TMLR
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    DS2TA: Denoising Spiking Transformer with Attenuated Spatiotemporal Attention
    Boxun Xu, Hejia Geng, Yuxuan Yin, and Peng Li
    In Transactions on Machine Learning Research (TMLR, under review), 2024
  7. ICCAD’24
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    ADO-LLM: Analog Design Bayesian Optimization with In-Context Learning of Large Language Models
    Yuxuan Yin, Yu Wang, Boxun Xu, and Peng Li
    In ACM/IEEE International Conference on Computer-Aided Design (ICCAD), 2024
  8. COLM’26
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    LASER: Language Model Regression for Semi-Structured Workflow Resource and Runtime Estimation
    Yuxuan Yin, Shengke Zhou, Yunjie Zhang, Ajay Mohindra, Boxun Xu, and Peng Li
    In Conference on Language Modeling (COLM, under review), 2026
  9. ITC’25
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    Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing
    Yuxuan Yin, Rebecca Chen, Boxun Xu, Chen He, and Peng Li
    In ACM/IEEE International Test Conference (ITC), 2025
  10. JSSC’24
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    AIMMI: Audio and Image Multi-Modal Intelligence via a Low-Power SoC With 2-MByte On-Chip MRAM for IoT Devices
    Zichen Fan, Hyochan An, Qirui Zhang, Boxun Xu, Li Xu, Chien-Wei Tseng, Yimai Peng, Ang Cao, Bowen Liu, Changwoo Lee, Zhehong Wang, Hun-Seok Kim, David Blaauw, and Dennis Sylvester
    In IEEE Journal of Solid-State Circuits(JSSC), 2024
  11. VLSI’22
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    Audio and Image Cross-Modal Intelligence via a 10TOPS/W 22nm SoC with Back-Propagation and Dynamic Power Gating
    Zichen Fan, Hyochan An, Qirui Zhang, Boxun Xu, Li Xu, Chien-Wei Tseng, Yimai Peng, Ang Cao, Bowen Liu, Changwoo Lee, Zhehong Wang, Fanghao Liu, Guanru Wang, Shenghao Jiang, Hun-Seok Kim, David Blaauw, and Dennis Sylvester
    In 2022 IEEE Symposium on VLSI Technology and Circuits (VLSI-Symposium), 2022

Other Publications

  1. AAAI’26
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    Khan-GCL: Kolmogorov-Arnold Network Based Graph Contrastive Learning with Hard Negatives
    Zihu Wang, Boxun Xu, Hejia Geng, and Peng Li
    In AAAI Conference on Artificial Intelligence (main track)(Acceptance Rate: 17.6%) , 2026

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