Micronets: a model for decentralising control in asynchronous processor architectures. - D. K. Arvind 001; Robert D. Mullins; Vinod E. F. Rebello (ASYNC, 1995)

A Fully Asynchronous Superscalar Architecture. - D. K. Arvind 001; Robert D. Mullins (IEEE PACT, 1999)

Self-Calibrating Clocks for Globally Asynchronous Locally Synchronous Systems. - Simon W. Moore; George S. Taylor; Paul A. Cunningham; Robert D. Mullins; Peter Robinson 001 (ICCD, 2000)

Improving Smart Card Security Using Self-Timed Circuits. - Simon W. Moore; Robert D. Mullins; Paul A. Cunningham; Ross J. Anderson; George S. Taylor (ASYNC, 2002)

Point to Point GALS Interconnect. - George S. Taylor; Simon W. Moore; Robert D. Mullins; Peter Robinson 001 (ASYNC, 2002)

Security Evaluation of Asynchronous Circuits. - Jacques J. A. Fournier; Simon W. Moore; Huiyun Li; Robert D. Mullins; George S. Taylor (CHES, 2003)

Balanced self-checking asynchronous logic for smart card applications. - Simon W. Moore; Ross J. Anderson; Robert D. Mullins; George S. Taylor; Jacques J. A. Fournier (Microprocess. Microsystems, 2003)

Low-Latency Virtual-Channel Routers for On-Chip Networks. - Robert D. Mullins; Andrew West; Simon W. Moore (ISCA, 2004)

The design and implementation of a low-latency on-chip network. - Robert D. Mullins; Andrew West; Simon W. Moore (ASP-DAC, 2006)

Demystifying Data-Driven and Pausible Clocking Schemes. - Robert D. Mullins; Simon W. Moore (ASYNC, 2007)

A Power and Energy Exploration of Network-on-Chip Architectures. - Arnab Banerjee; Robert D. Mullins; Simon W. Moore (NOCS, 2007)

A Network of Time-Division Multiplexed Wiring for FPGAs. - Rosemary M. Francis; Simon W. Moore; Robert D. Mullins (NOCS, 2008)

An Energy and Performance Exploration of Network-on-Chip Architectures. - Arnab Banerjee; Pascal T. Wolkotte; Robert D. Mullins; Simon W. Moore; Gerard J. M. Smit (IEEE Trans. Very Large Scale Integr. Syst., 2009)

Designing a Physical Locality Aware Coherence Protocol for Chip-Multiprocessors. - Christian Fensch; Nick Barrow-Williams; Robert D. Mullins; Simon W. Moore (IEEE Trans. Computers, 2013)

Exploiting Tightly-Coupled Cores. - Daniel Bates; Alex Bradbury; Andreas Koltes; Robert D. Mullins (J. Signal Process. Syst., 2015)

Performance implications of transient loop-carried data dependences in automatically parallelized loops. - Niall Murphy; Timothy M. Jones 001; Robert D. Mullins; Simone Campanoni (CC, 2016)

Configurable memory systems for embedded many-core processors. - Daniel Bates; Alexandra W. Chadwick; Robert D. Mullins (CoRR, 2016)

1D-FALCON: Accelerating Deep Convolutional Neural Network Inference by Co-optimization of Models and Underlying Arithmetic Implementation. - Partha Maji; Robert D. Mullins (ICANN (2), 2017)

ADaPT: optimizing CNN inference on IoT and mobile devices using approximately separable 1-D kernels. - Partha Maji; Daniel Bates; Alexandra W. Chadwick; Robert D. Mullins (IML, 2017)

Mayo: A Framework for Auto-generating Hardware Friendly Deep Neural Networks. - Yiren Zhao; Xitong Gao; Robert D. Mullins; Chengzhong Xu 001 (EMDL@MobiSys, 2018)

Next generation single board clusters. - Jeremy Singer; Herry Herry; Philip James Basford; Wajdi Hajji; Colin S. Perkins; Fung Po Tso 001; Dimitrios Pezaros; Robert D. Mullins; Eiko Yoneki; Simon J. Cox 001; Steven J. Johnston (NOMS, 2018)

The Taboo Trap: Behavioural Detection of Adversarial Samples. - Ilia Shumailov; Yiren Zhao; Robert D. Mullins; Ross Anderson 001 (CoRR, 2018)

On the Reduction of Computational Complexity of Deep Convolutional Neural Networks. - Partha Maji; Robert D. Mullins (Entropy, 2018)

Commodity single board computer clusters and their applications. - Steven J. Johnston; Philip James Basford; Colin S. Perkins; Herry Herry; Fung Po Tso 001; Dimitrios Pezaros; Robert D. Mullins; Eiko Yoneki; Simon J. Cox 001; Jeremy Singer (Future Gener. Comput. Syst., 2018)

Efficient Winograd or Cook-Toom Convolution Kernel Implementation on Widely Used Mobile CPUs. - Partha Maji; Andrew Mundy; Ganesh Dasika; Jesse G. Beu; Matthew Mattina; Robert D. Mullins (EMC2@HPCA/CVPR/ISCA, 2019)

Automatic Generation of Multi-Precision Multi-Arithmetic CNN Accelerators for FPGAs. - Yiren Zhao; Xitong Gao; Xuan Guo; Junyi Liu; Erwei Wang; Robert D. Mullins; Peter Y. K. Cheung; George A. Constantinides; Cheng-Zhong Xu 001 (FPT, 2019)

Dynamic Channel Pruning: Feature Boosting and Suppression. - Xitong Gao; Yiren Zhao; Lukasz Dudziak; Robert D. Mullins; Cheng-Zhong Xu 001 (ICLR (Poster), 2019)

Characterizing Sources of Ineffectual Computations in Deep Learning Networks. - Milos Nikolic 002; Mostafa Mahmoud; Andreas Moshovos; Yiren Zhao; Robert D. Mullins (ISPASS, 2019)

To Compress Or Not To Compress: Understanding The Interactions Between Adversarial Attacks And Neural Network Compression. - Yiren Zhao; Ilia Shumailov; Robert D. Mullins; Ross Anderson 001 (SysML, 2019)

Focused Quantization for Sparse CNNs. - Yiren Zhao; Xitong Gao; Daniel Bates; Robert D. Mullins; Cheng-Zhong Xu 001 (NeurIPS, 2019)

Sitatapatra: Blocking the Transfer of Adversarial Samples. - Ilia Shumailov; Xitong Gao; Yiren Zhao; Robert D. Mullins; Ross Anderson 001; Cheng-Zhong Xu 001 (CoRR, 2019)

Efficient and Effective Quantization for Sparse DNNs. - Yiren Zhao; Xitong Gao; Daniel Bates; Robert D. Mullins; Cheng-Zhong Xu 001 (CoRR, 2019)

Fast TLB Simulation for RISC-V Systems. - Xuan Guo; Robert D. Mullins (CoRR, 2019)

Towards Certifiable Adversarial Sample Detection. - Ilia Shumailov; Yiren Zhao; Robert D. Mullins; Ross J. Anderson (AISec@CCS, 2020)

Blackbox Attacks on Reinforcement Learning Agents Using Approximated Temporal Information. - Yiren Zhao; Ilia Shumailov; Han Cui; Xitong Gao; Robert D. Mullins; Ross J. Anderson (DSN Workshops, 2020)

Probabilistic Dual Network Architecture Search on Graphs. - Yiren Zhao; Duo Wang; Xitong Gao; Robert D. Mullins; Pietro Liò; Mateja Jamnik (CoRR, 2020)

Accelerate Cycle-Level Full-System Simulation of Multi-Core RISC-V Systems with Binary Translation. - Xuan Guo; Robert D. Mullins (CoRR, 2020)

Learned Low Precision Graph Neural Networks. - Yiren Zhao; Duo Wang; Daniel Bates; Robert D. Mullins; Mateja Jamnik; Pietro Liò (CoRR, 2020)

Nudge Attacks on Point-Cloud DNNs. - Yiren Zhao; Ilia Shumailov; Robert D. Mullins; Ross J. Anderson (CoRR, 2020)

Performance analysis of single board computer clusters. - Philip James Basford; Steven J. Johnston; Colin S. Perkins; Tony Garnock-Jones; Fung Po Tso 001; Dimitrios Pezaros; Robert D. Mullins; Eiko Yoneki; Jeremy Singer; Simon J. Cox 001 (Future Gener. Comput. Syst., 2020)

Sponge Examples: Energy-Latency Attacks on Neural Networks. - Ilia Shumailov; Yiren Zhao; Daniel Bates; Nicolas Papernot; Robert D. Mullins; Ross Anderson 001 (EuroS&P, 2021)

Lane Compression: A Lightweight Lossless Compression Method for Machine Learning on Embedded Systems. - Yousun Ko 001; Alexandra W. Chadwick; Daniel Bates; Robert D. Mullins (ACM Trans. Embed. Comput. Syst., 2021)

DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning. - Robert Hönig; Yiren Zhao; Robert D. Mullins (ICML, 2022)

Trace-and-brace (TAB): bespoke software countermeasures against soft errors. - Yousun Ko 001; Alex Bradbury; Bernd Burgstaller; Robert D. Mullins (LCTES, 2022)

Rapid Model Architecture Adaption for Meta-Learning. - Yiren Zhao; Xitong Gao; Ilia Shumailov; Nicolò Fusi; Robert D. Mullins (NeurIPS, 2022)

Model Architecture Adaption for Bayesian Neural Networks. - Duo Wang; Yiren Zhao; Ilia Shumailov; Robert D. Mullins (CoRR, 2022)

Muntjac - Open Source Multicore RV64 Linux-capable SoC. - Xuan Guo; Daniel Bates; Robert D. Mullins; Alex Bradbury (CoRR, 2022)

Efficient Adversarial Training With Data Pruning. - Maximilian Kaufmann; Yiren Zhao; Ilia Shumailov; Robert D. Mullins; Nicolas Papernot (CoRR, 2022)

Revisiting Embeddings for Graph Neural Networks. - Skye Purchase; Aaron Zhao; Robert D. Mullins (CoRR, 2022)

Augmentation Backdoors. - Joseph Rance; Yiren Zhao; Ilia Shumailov; Robert D. Mullins (CoRR, 2022)

ImpNet: Imperceptible and blackbox-undetectable backdoors in compiled neural networks. - Tim Clifford; Ilia Shumailov; Yiren Zhao; Ross J. Anderson; Robert D. Mullins (CoRR, 2022)

Wide Attention Is The Way Forward For Transformers. - Jason Ross Brown; Yiren Zhao; Ilia Shumailov; Robert D. Mullins (CoRR, 2022)

DARTFormer: Finding The Best Type Of Attention. - Jason Ross Brown; Yiren Zhao; Ilia Shumailov; Robert D. Mullins (CoRR, 2022)

Sim-D: A SIMD Accelerator for Hard Real-Time Systems. - Roy Spliet; Robert D. Mullins (IEEE Trans. Computers, 2022)

Revisiting Automated Prompting: Are We Actually Doing Better? - Yulin Zhou; Yiren Zhao; Ilia Shumailov; Robert D. Mullins; Yarin Gal (ACL (2), 2023)

Revisiting Structured Dropout. - Yiren Zhao; Oluwatomisin Dada; Robert D. Mullins; Xitong Gao (ACML, 2023)

Architectural Backdoors in Neural Networks. - Mikel Bober-Irizar; Ilia Shumailov; Yiren Zhao; Robert D. Mullins; Nicolas Papernot (CVPR, 2023)

Dynamic Stashing Quantization for Efficient Transformer Training. - Guo Yang; Daniel Lo; Robert D. Mullins; Yiren Zhao (EMNLP (Findings), 2023)

Human-Producible Adversarial Examples. - David Khachaturov; Yue Gao 011; Ilia Shumailov; Robert D. Mullins; Ross J. Anderson; Kassem Fawaz (CoRR, 2023)

LLM4DV: Using Large Language Models for Hardware Test Stimuli Generation. - Zixi Zhang; Greg Chadwick; Hugo McNally; Yiren Zhao; Robert D. Mullins (CoRR, 2023)

Beyond Slow Signs in High-fidelity Model Extraction. - Hanna Foerster; Robert D. Mullins; Ilia Shumailov; Jamie Hayes (NeurIPS, 2024)

ImpNet: Imperceptible and blackbox-undetectable backdoors in compiled neural networks. - Eleanor Clifford; Ilia Shumailov; Yiren Zhao; Ross J. Anderson; Robert D. Mullins (SaTML, 2024)

Unlocking the Global Synergies in Low-Rank Adapters. - Zixi Zhang; Cheng Zhang; Xitong Gao; Robert D. Mullins; George A. Constantinides; Yiren Zhao (CoRR, 2024)

Optimised Grouped-Query Attention Mechanism for Transformers. - Yuang Chen; Cheng Zhang; Xitong Gao; Robert D. Mullins; George A. Constantinides; Yiren Zhao (CoRR, 2024)

Complexity Matters: Effective Dimensionality as a Measure for Adversarial Robustness. - David Khachaturov; Robert D. Mullins (CoRR, 2024)

Hardware and Software Platform Inference. - Cheng Zhang; Hanna Foerster; Robert D. Mullins; Yiren Zhao; Ilia Shumailov (CoRR, 2024)

LLM4DV: Using Large Language Models for Hardware Test Stimuli Generation. - Zixi Zhang; Balint Szekely; Pedro Gimenes; Greg Chadwick; Hugo McNally; Jianyi Cheng; Robert D. Mullins; Yiren Zhao (FCCM, 2025)

Mascot: Predicting Memory Dependencies and Opportunities for Speculative Memory Bypassing. - Karl H. Mose; Sebastian S. Kim; Alberto Ros 001; Timothy M. Jones 001; Robert D. Mullins (HPCA, 2025)

Inverse Constitutional AI: Compressing Preferences into Principles. - Arduin Findeis; Timo Kaufmann; Eyke Hüllermeier; Samuel Albanie; Robert D. Mullins (ICLR, 2025)

Locking Machine Learning Models into Hardware. - Eleanor Clifford; Adhithya Saravanan; Harry Langford; Cheng Zhang; Yiren Zhao; Robert D. Mullins; Ilia Shumailov; Jamie Hayes (SaTML, 2025)

Architectural Neural Backdoors from First Principles. - Harry Langford; Ilia Shumailov; Yiren Zhao; Robert D. Mullins; Nicolas Papernot (SP, 2025)

"I am bad": Interpreting Stealthy, Universal and Robust Audio Jailbreaks in Audio-Language Models. - Isha Gupta; David Khachaturov; Robert D. Mullins (CoRR, 2025)

Watermarking Needs Input Repetition Masking. - David Khachaturov; Robert D. Mullins; Ilia Shumailov; Sumanth Dathathri (CoRR, 2025)

Adversarial Suffix Filtering: a Defense Pipeline for LLMs. - David Khachaturov; Robert D. Mullins (CoRR, 2025)

Governments Should Mandate Tiered Anonymity on Social-Media Platforms to Counter Deepfakes and LLM-Driven Mass Misinformation. - David Khachaturov; Roxanne Schnyder; Robert D. Mullins (CoRR, 2025)

Learning from Preferences and Mixed Demonstrations in General Settings. - Jason Ross Brown; Carl Henrik Ek; Robert D. Mullins (CoRR, 2025)