EdgeBERT: Optimizing On-Chip Inference for Multi-Task NLP. - Thierry Tambe; Coleman Hooper; Lillian Pentecost; En-Yu Yang; Marco Donato; Victor Sanh; Alexander M. Rush; David Brooks 001; Gu-Yeon Wei (CoRR, 2020)

SM6: A 16nm System-on-Chip for Accurate and Noise-Robust Attention-Based NLP Applications : The 33rd Hot Chips Symposium - August 22-24, 2021. - Thierry Tambe; En-Yu Yang; Glenn G. Ko; Yuji Chai; Coleman Hooper; Marco Donato; Paul N. Whatmough; Alexander M. Rush; David Brooks 001; Gu-Yeon Wei (HCS, 2021)

9.8 A 25mm2 SoC for IoT Devices with 18ms Noise-Robust Speech-to-Text Latency via Bayesian Speech Denoising and Attention-Based Sequence-to-Sequence DNN Speech Recognition in 16nm FinFET. - Thierry Tambe; En-Yu Yang; Glenn G. Ko; Yuji Chai; Coleman Hooper; Marco Donato; Paul N. Whatmough; Alexander M. Rush; David Brooks 001; Gu-Yeon Wei (ISSCC, 2021)

EdgeBERT: Sentence-Level Energy Optimizations for Latency-Aware Multi-Task NLP Inference. - Thierry Tambe; Coleman Hooper; Lillian Pentecost; Tianyu Jia; En-Yu Yang; Marco Donato; Victor Sanh; Paul N. Whatmough; Alexander M. Rush; David Brooks 001; Gu-Yeon Wei (MICRO, 2021)

Quantifying and Maximizing the Benefits of Back-End Noise Adaption on Attention-Based Speech Recognition Models. - Coleman Hooper; Thierry Tambe; Gu-Yeon Wei (CoRR, 2021)

A 12nm 18.1TFLOPs/W Sparse Transformer Processor with Entropy-Based Early Exit, Mixed-Precision Predication and Fine-Grained Power Management. - Thierry Tambe; Jeff Zhang 001; Coleman Hooper; Tianyu Jia; Paul N. Whatmough; Joseph Zuckerman; Maico Cassel dos Santos; Erik Jens Loscalzo; Davide Giri; Kenneth L. Shepard; Luca P. Carloni; Alexander M. Rush; et al. (ISSCC, 2023)

Full Stack Optimization of Transformer Inference: a Survey. - Sehoon Kim 001; Coleman Hooper; Thanakul Wattanawong; Minwoo Kang; Ruohan Yan; Hasan Genc; Grace Dinh; Qijing Huang 001; Kurt Keutzer; Michael W. Mahoney; Yakun Sophia Shao; Amir Gholami (CoRR, 2023)

SPEED: Speculative Pipelined Execution for Efficient Decoding. - Coleman Hooper; Sehoon Kim 001; Hiva Mohammadzadeh; Hasan Genc; Kurt Keutzer; Amir Gholami; Yakun Sophia Shao (CoRR, 2023)

Property-Aware Multi-Speaker Data Simulation: A Probabilistic Modelling Technique for Synthetic Data Generation. - Taejin Park; He Huang 012; Coleman Hooper; Nithin Rao Koluguri; Kunal Dhawan; Ante Jukic; Jagadeesh Balam; Boris Ginsburg (CoRR, 2023)

S-LoRA: Serving Thousands of Concurrent LoRA Adapters. - Ying Sheng 007; Shiyi Cao; Dacheng Li; Coleman Hooper; Nicholas Lee; Shuo Yang; Christopher Chou; Banghua Zhu; Lianmin Zheng; Kurt Keutzer; Joseph E. Gonzalez; Ion Stoica (CoRR, 2023)

A 16-nm SoC for Noise-Robust Speech and NLP Edge AI Inference With Bayesian Sound Source Separation and Attention-Based DNNs. - Thierry Tambe; En-Yu Yang; Glenn G. Ko; Yuji Chai; Coleman Hooper; Marco Donato; Paul N. Whatmough; Alexander M. Rush; David Brooks 001; Gu-Yeon Wei (IEEE J. Solid State Circuits, 2023)

SqueezeLLM: Dense-and-Sparse Quantization. - Sehoon Kim 001; Coleman Hooper; Amir Gholami; Zhen Dong 003; Xiuyu Li; Sheng Shen 001; Michael W. Mahoney; Kurt Keutzer (ICML, 2024)

SLoRA: Scalable Serving of Thousands of LoRA Adapters. - Ying Sheng 007; Shiyi Cao; Dacheng Li; Coleman Hooper; Nicholas Lee; Shuo Yang; Christopher Chou; Banghua Zhu; Lianmin Zheng; Kurt Keutzer; Joseph Gonzalez 001; Ion Stoica (MLSys, 2024)

KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization. - Coleman Hooper; Sehoon Kim 001; Hiva Mohammadzadeh; Michael W. Mahoney; Yakun Sophia Shao; Kurt Keutzer; Amir Gholami (NeurIPS, 2024)

Learned Best-Effort LLM Serving. - Siddharth Jha; Coleman Hooper; Xiaoxuan Liu; Sehoon Kim 001; Kurt Keutzer (CoRR, 2024)

TinyAgent: Function Calling at the Edge. - Lutfi Eren Erdogan; Nicholas Lee; Siddharth Jha; Sehoon Kim 001; Ryan Tabrizi; Suhong Moon; Coleman Hooper; Gopala Anumanchipalli; Kurt Keutzer; Amir Gholami (CoRR, 2024)

Squeezed Attention: Accelerating Long Context Length LLM Inference. - Coleman Hooper; Sehoon Kim 001; Hiva Mohammadzadeh; Monishwaran Maheswaran; June Paik; Michael W. Mahoney; Kurt Keutzer; Amir Gholami (CoRR, 2024)

AI and Memory Wall. - Amir Gholami; Zhewei Yao; Sehoon Kim 001; Coleman Hooper; Michael W. Mahoney; Kurt Keutzer (IEEE Micro, 2024)

Squeezed Attention: Accelerating Long Context Length LLM Inference. - Coleman Richard Charles Hooper; Sehoon Kim 001; Hiva Mohammadzadeh; Monishwaran Maheswaran; Sebastian Zhao; June Paik; Michael W. Mahoney; Kurt Keutzer; Amir Gholami (ACL (1), 2025)

QuantSpec: Self-Speculative Decoding with Hierarchical Quantized KV Cache. - Rishabh Tiwari; Haocheng Xi; Aditya Tomar; Coleman Hooper; Sehoon Kim 001; Maxwell Horton; Mahyar Najibi; Michael W. Mahoney; Kurt Keutzer; Amir Gholami (CoRR, 2025)

ETS: Efficient Tree Search for Inference-Time Scaling. - Coleman Hooper; Sehoon Kim 001; Suhong Moon; Kerem Dilmen; Monishwaran Maheswaran; Nicholas Lee; Michael W. Mahoney; Yakun Sophia Shao; Kurt Keutzer; Amir Gholami (CoRR, 2025)

FGMP: Fine-Grained Mixed-Precision Weight and Activation Quantization for Hardware-Accelerated LLM Inference. - Coleman Hooper; Charbel Sakr; Ben Keller; Rangharajan Venkatesan; Kurt Keutzer; Yakun Sophia Shao; Brucek Khailany (CoRR, 2025)

Multipole Attention for Efficient Long Context Reasoning. - Coleman Hooper; Sebastian Zhao; Luca Manolache; Sehoon Kim 001; Michael W. Mahoney; Yakun Sophia Shao; Kurt Keutzer; Amir Gholami (CoRR, 2025)

XQuant: Breaking the Memory Wall for LLM Inference with KV Cache Rematerialization. - Aditya Tomar; Coleman Hooper; Minjae Lee; Haocheng Xi; Rishabh Tiwari; Wonjun Kang; Luca Manolache; Michael W. Mahoney; Kurt Keutzer; Amir Gholami (CoRR, 2025)