Selected Publications
(Check my Google Scholar page for the full list)
Machine learning and NLP
- Kazi Ahmed Asif Fuad, and Lizhong Chen, "LLM-Ref: Enhancing Reference Handling in Technical Writing with Large Language Models", arXiv:2411.00294, 2024.
- Yifan Zeng, Ojas Tendolkar, Raymond Baartmans, Qingyun Wu, Huazheng Wang, and Lizhong Chen, "LLM-RankFusion: Mitigating Intrinsic Inconsistency in LLM-based Ranking", arXiv:2406.00231, 2024.
- Matthew Raffel, Victor Agostinelli, and Lizhong Chen, "Simultaneous Masking, Not Prompting Optimization: A Paradigm Shift in Fine-tuning LLMs for Simultaneous Translation", Empirical Methods in Natural Language Processing (EMNLP), 2024.
- Victor Agostinelli, Max Wild, Matthew Raffel, Kazi Asif Fuad, and Lizhong Chen, "Simul-LLM: A Framework for Exploring High-Quality Simultaneous Translation with Large Language Models", Proceedings of the Association for Computational Linguistics (ACL), 2024.
- Victor Agostinelli, Sanghyun Hong, and Lizhong Chen, LeaPformer: Enabling Linear Transformers for Autoregressive and Simultaneous Tasks via Learned Proportions, International Conference on Machine Learning Representations (ICML), 2024.
- Victor Agostinelli, and Lizhong Chen, "Improving Autoregressive NLP Tasks via Modular Linearized Attention", European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML), 2023.
- Matthew Raffel, Drew Penney, and Lizhong Chen, "Shiftable Context: Addressing Training-Inference Context Mismatch in Simultaneous Speech Translation", International Conference on Machine Learning Representations (ICML), 2023.
- Matthew Raffel, and Lizhong Chen, "Implicit Memory Transformer for Computationally Efficient Simultaneous Speech Translation", Findings of the Association for Computational Linguistics (ACL Findings), 2023.
- Tianhong Huang, Victor Agostinelli, and Lizhong Chen, "Partitioning-Guided K-Means: Extreme Empty Cluster Resolution for Extreme Model Compression", arxiv 2306.14031, 2023.
Computer systems and architecture
- Andrew Ensinger, Gabriel Kulp, Victor Agostinelli, Dennis Lyakhov, and Lizhong Chen, "Swift: High-Performance Sparse Tensor Contraction for Scientific Applications", arXiv:2410.10094, 2024.
- Gabriel Kulp, Andrew Ensinger, and Lizhong Chen, "FLAASH: Flexible Accelerator Architecture for Sparse High-Order Tensor Contraction", arXiv 2404.16317, 2024.
- Drew Penney, Bin Li, Lizhong Chen, et al., "RAPID: Enabling fast online policy learning in dynamic public cloud environments", Neurocomputing, 2023.
- Drew Penney, Bin Li, Jaroslaw Sydir, Charlie Tai, Eoin Walsh, Tommy Long, Stefan Lee, and Lizhong Chen, "PROMPT: Learning Dynamic Resource Allocation Policies for Network Applications", Future Generation Computer Systems (FGCS), 2023.
- Kazi Ahmed Asif Fuad, and Lizhong Chen, "A Survey on Sparsity Exploration in Transformer-Based Accelerators", Electronics, 2022.
- Arash Azizimazreah, and Lizhong Chen, "Polymorphic Accelerators for Deep Neural Networks", IEEE Transactions on Computers (TC), 2021.
- Yongbin Gu, Wenxuan Wu, Yunfan Li, and Lizhong Chen, "UVMBench: A Comprehensive Benchmark Suite for Researching Unified Virtual Memory in GPUs", arXiv 2007.09822, July 2020.
- Ting-Ru Lin, Drew Penney, Massoud Pedram, and Lizhong Chen "A Deep Reinforcement Learning Framework for Architectural Exploration: A Routerless NoC Case Study", to appear in the 26th IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2020 (Best Paper Runner-up Award).
- Yunfan Li, and Lizhong Chen, "EquiNox: Equivalent NoC Injection Routers for Silicon Interposer-based Many-core Accelerators", to appear in the 26th IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2020.
- Drew Penney, and Lizhong Chen, "A Survey of Machine Learning Applied to Computer Architecture Design", arXiv 1909.12373, September 2019.
- Yunfan Li, Drew Penney, Abhishek Ramamurthy, and Lizhong Chen, "Characterizing On-Chip Traffic Patterns in General-Purpose GPUs: A Deep Learning Approach", to appear in Proc. of the 36th IEEE International Conference on Computer Design (ICCD), 2019.
- Yongbin Gu, and Lizhong Chen, "Dynamically Linked MSHRs for Adaptive Miss Handling in GPUs", in Proc. of the ACM International Conference on Supercomputing (ICS), June 2019.
- Arash Azizimazreah, and Lizhong Chen, "Shortcut Mining: Exploiting Cross-layer Shortcut Reuse in DCNN Accelerators", in the 25th IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2019.
- Arash Azizimazreah, Yongbin Gu, Xiang Gu, and Lizhong Chen, "Tolerating Soft Errors in Deep Learning Accelerators with Reliable On-Chip Memory Designs", in the 13th IEEE International Conference on Networking, Architecture, and Storage (NAS), 2018 (Best Paper Candidate).
- Fawaz Alazemi, Arash Azizimazreah, Bella Bose, and Lizhong Chen, "Routerless Networks-on-Chip", in the 24th IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2018.
- Aosen Wang, Lizhong Chen, and Wenyao Xu, "XPro: A Cross-End Processing Architecture for Data Analytics in Wearables", in the IEEE/ACM International Symposium on Computer Architecture (ISCA), 2017.
- Di Zhu, Siyu Yue, Massoud Pedram, and Lizhong Chen, "CALM: contention-aware latency-minimal application mapping for flattened butterfly on-chip networks", in ACM Transactions on Design Automation of Electronic Systems (TODAES), 2017.
- Lizhong Chen, Di Zhu, Massoud Pedram, and Timothy M. Pinkston, "Simulation of NoC Power-Gating: Requirements, Optimizations, and the Agate Simulator", in Journal of Parallel and Distributed Computing (JPDC), 2016.
- Di Zhu, Lizhong Chen, Siyu Yue, Timothy M. Pinkston, and Massoud Pedram, "Providing Balanced Mapping for Multiple Applications in Many-Core Chip Multiprocessors", IEEE Transactions on Computers (TC), 2016.
- Lihang Zhao, Lizhong Chen, Woojin Choi, and Jeffery Draper, "A Filtering Mechanism to Reduce Network Bandwidth Utilization of Transaction Execution", in the ACM Transactions on Architecture and Code Optimization (TACO), 2016.
- Lizhong Chen, Di Zhu, Massoud Pedram, and Timothy M. Pinkston, "Power Punch: Towards Non-blocking Power-gating of NoC Routers", in Proc. of the 21st IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2015.
- Ruisheng Wang, and Lizhong Chen, "Futility Scaling: High-Associativity Cache Partitioning", in Proc. of the 47th IEEE/ACM International Symposium on Microarchitecture (MICRO), December 2014.
- Lizhong Chen, Lihang Zhao, Ruisheng Wang, and Timothy Pinkston, "MP3: Minimizing Performance Penalty for Power-gating of Clos Network-on-Chip", in Proc. of the 20th IEEE International Symposium on High-Performance Computer Architecture (HPCA), February 2014.
- Ruisheng Wang, Lizhong Chen, and Timothy Pinkston, "Bubble Coloring: Avoiding Routing- and Protocol-induced Deadlocks With Minimal Virtual Channel Requirement", in Proc. of the ACM International Conference on Supercomputing (ICS), June 2013.
- Lizhong Chen, and Timothy Pinkston, "Worm-bubble Flow Control", in Proc. of the 19th IEEE International Symposium on High-Performance Computer Architecture (HPCA), February 2013.
- Lihang Zhao, Woojin Choi, Lizhong Chen, and Jeffery Draper, "In-Network Traffic Regulation for Transactional Memory", in Proc. of the 19th IEEE International Symposium on High-Performance Computer Architecture (HPCA), February 2013.
- Lizhong Chen, Ruisheng Wang, and Timothy Pinkston, "Efficient Implementation of Globally-aware Network Flow Control", in Journal of Parallel and Distributed Computing (JPDC), volume 72, issue 11, 2012.
- Lizhong Chen, and Timothy Pinkston, "NoRD: Node-Router Decoupling for Effective Power-gating of On-Chip Routers", in Proc. of the 45th IEEE/ACM International Symposium on Microarchitecture (MICRO), December 2012.
Disclaimer
Permission to make copies of all or part of this material is granted without fee provided that copies are not made or distributed for profit or commercial advantage. To copy otherwise, or to repost, requires prior permission of the copyright holders.