An efficient implementation of online arithmetic. - Yiren Zhao; John Wickerson; George A. Constantinides (FPT, 2016)

Redundancy-Reduced MobileNet Acceleration on Reconfigurable Logic for ImageNet Classification. - Jiang Su; Julian Faraone; Junyi Liu; Yiren Zhao; David B. Thomas; Philip Heng Wai Leong; Peter Y. K. Cheung (ARC, 2018)

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

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

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)

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)

Pay Attention to Features, Transfer Learn Faster CNNs. - Kafeng Wang; Xitong Gao; Yiren Zhao; Xingjian Li 002; Dejing Dou; Cheng-Zhong Xu 001 (ICLR, 2020)

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

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)

Markpainting: Adversarial Machine Learning meets Inpainting. - David Khachaturov; Ilia Shumailov; Yiren Zhao; Nicolas Papernot; Ross J. Anderson (ICML, 2021)

Manipulating SGD with Data Ordering Attacks. - Ilia Shumailov; Zakhar Shumaylov; Dmitry Kazhdan; Yiren Zhao; Nicolas Papernot; Murat A. Erdogdu; Ross J. Anderson (NeurIPS, 2021)

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

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

Flareon: Stealthy any2any Backdoor Injection via Poisoned Augmentation. - Tianrui Qin; Xianghuan He; Xitong Gao; Yiren Zhao; Kejiang Ye; Cheng-Zhong Xu 001 (CoRR, 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)

Adaptive Channel Sparsity for Federated Learning under System Heterogeneity. - Dongping Liao; Xitong Gao; Yiren Zhao; Chengzhong Xu 001 (CVPR, 2023)

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

Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM Inference? - Cheng Zhang; Jianyi Cheng; Ilia Shumailov; George A. Constantinides; Yiren Zhao (EMNLP, 2023)

Will More Expressive Graph Neural Networks Do Better on Generative Tasks? - Xiandong Zou; Xiangyu Zhao; Pietro Lio; Yiren Zhao (LoG, 2023)

MiliPoint: A Point Cloud Dataset for mmWave Radar. - Han Cui; Shu Zhong; Jiacheng Wu; Zichao Shen; Naim Dahnoun; Yiren Zhao (NeurIPS, 2023)

FlexWAN: Software Hardware Co-design for Cost-Effective and Resilient Optical Backbones. - Congcong Miao; Zhizhen Zhong; Ying Zhang 022; Kunling He; Fangchao Li; Minggang Chen; Yiren Zhao; Xiang Li; Zekun He; Xianneng Zou; Jilong Wang 001 (SIGCOMM, 2023)

Task-Agnostic Graph Neural Network Evaluation via Adversarial Collaboration. - Xiangyu Zhao; Hannes Stärk; Dominique Beaini; Pietro Liò; Yiren Zhao (CoRR, 2023)

The Curse of Recursion: Training on Generated Data Makes Models Forget. - Ilia Shumailov; Zakhar Shumaylov; Yiren Zhao; Yarin Gal; Nicolas Papernot; Ross J. Anderson (CoRR, 2023)

Hybrid Graph: A Unified Graph Representation with Datasets and Benchmarks for Complex Graphs. - Zehui Li; Xiangyu Zhao; Mingzhu Shen; Guy-Bart Stan; Pietro Liò; Yiren Zhao (CoRR, 2023)

Genomic Interpreter: A Hierarchical Genomic Deep Neural Network with 1D Shifted Window Transformer. - Zehui Li; Akashaditya Das; William A. V. Beardall; Yiren Zhao; Guy-Bart Stan (CoRR, 2023)

Fast Prototyping Next-Generation Accelerators for New ML Models using MASE: ML Accelerator System Exploration. - Jianyi Cheng; Cheng Zhang; Zhewen Yu; Alexander Montgomerie-Corcoran; Can Xiao; Christos-Savvas Bouganis; Yiren Zhao (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)

Latent Diffusion Model for DNA Sequence Generation. - Zehui Li; Yuhao Ni; Tim August B. Huygelen; Akashaditya Das; Guoxuan Xia; Guy-Bart Stan; Yiren Zhao (CoRR, 2023)

Enhancing Node Representations for Real-World Complex Networks with Topological Augmentation. - Xiangyu Zhao; Zehui Li; Mingzhu Shen; Guy-Bart Stan; Pietro Liò; Yiren Zhao (ECAI, 2024)

HASS: Hardware-Aware Sparsity Search for Dataflow DNN Accelerator. - Zhewen Yu; Sudarshan Sreeram; Krish Agrawal; Junyi Wu; Alexander Montgomerie-Corcoran; Cheng Zhang; Jianyi Cheng; Christos-Savvas Bouganis; Yiren Zhao (FPL, 2024)

LQER: Low-Rank Quantization Error Reconstruction for LLMs. - Cheng Zhang; Jianyi Cheng; George Anthony Constantinides; Yiren Zhao (ICML, 2024)

Absorb & Escape: Overcoming Single Model Limitations in Generating Heterogeneous Genomic Sequences. - Zehui Li; Yuhao Ni; Guoxuan Xia; William A. V. Beardall; Akashaditya Das; Guy-Bart Stan; Yiren Zhao (NeurIPS, 2024)

GV-Rep: A Large-Scale Dataset for Genetic Variant Representation Learning. - Zehui Li; Vallijah Subasri; Guy-Bart Stan; Yiren Zhao; Bo Wang (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)

Verification and Fault Injection Platform Based on MTB Stimulus Generation Method for L2 Deep Market Quote Decoder. - Le Yu; Zhiheng Liang; Yaqi Li; Shiwei Zhang; Yiren Zhao; Peter Y. K. Cheung (IEEE Access, 2024)

DiscDiff: Latent Diffusion Model for DNA Sequence Generation. - Zehui Li; Yuhao Ni; William A. V. Beardall; Guoxuan Xia; Akashaditya Das; Guy-Bart Stan; Yiren Zhao (CoRR, 2024)

Enhancing Real-World Complex Network Representations with Hyperedge Augmentation. - Xiangyu Zhao; Zehui Li; Mingzhu Shen; Guy-Bart Stan; Pietro Liò; Yiren Zhao (CoRR, 2024)

Δ-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers. - Pengtao Chen; Mingzhu Shen; Peng Ye 006; Jianjian Cao; Chongjun Tu; Christos-Savvas Bouganis; Yiren Zhao; Tao Chen 003 (CoRR, 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)

Scaling Laws for Mixed quantization in Large Language Models. - Zeyu Cao; Cheng Zhang; Pedro Gimenes; Jianqiao Lu; Jianyi Cheng; Yiren Zhao (CoRR, 2024)

Absorb & Escape: Overcoming Single Model Limitations in Generating Genomic Sequences. - Zehui Li; Yuhao Ni; Guoxuan Xia; William A. V. Beardall; Akashaditya Das; Guy-Bart Stan; Yiren Zhao (CoRR, 2024)

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

AI models collapse when trained on recursively generated data. - Ilia Shumailov; Zakhar Shumaylov; Yiren Zhao; Nicolas Papernot; Ross J. Anderson; Yarin Gal (Nat., 2024)

Refining Salience-Aware Sparse Fine-Tuning Strategies for Language Models. - Xinxin Liu; Aaron Thomas; Cheng Zhang; Jianyi Cheng; Yiren Zhao; Xitong Gao (ACL (1), 2025)

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)

Flexnetic: Cost-Effective and Smooth Evolution of Optical Backbone. - Zhiquan Wang; Congcong Miao; Yiren Zhao; Kunling He; Jilong Wang 001 (ICCCN, 2025)

QERA: an Analytical Framework for Quantization Error Reconstruction. - Cheng Zhang; Jeffrey T. H. Wong; Can Xiao; George Anthony Constantinides; Yiren Zhao (ICLR, 2025)

Cached Multi-Lora Composition for Multi-Concept Image Generation. - Xiandong Zou; Mingzhu Shen; Christos-Savvas Bouganis; Yiren Zhao (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)

Omni-DNA: A Unified Genomic Foundation Model for Cross-Modal and Multi-Task Learning. - Zehui Li; Vallijah Subasri; Yifei Shen; Dongsheng Li; Yiren Zhao; Guy-Bart Stan; Caihua Shan (CoRR, 2025)

AMPLE: Event-Driven Accelerator for Mixed-Precision Inference of Graph Neural Networks. - Pedro Gimenes; Yiren Zhao; George A. Constantinides (CoRR, 2025)

ARIES: Autonomous Reasoning with LLMs on Interactive Thought Graph Environments. - Pedro Gimenes; Zeyu Cao; Jeffrey Wong; Yiren Zhao (CoRR, 2025)

A3 : an Analytical Low-Rank Approximation Framework for Attention. - Jeffrey T. H. Wong; Cheng Zhang; Xinye Cao; Pedro Gimenes; George A. Constantinides; Wayne Luk; Yiren Zhao (CoRR, 2025)

Mixture of Weight-shared Heterogeneous Group Attention Experts for Dynamic Token-wise KV Optimization. - Guanghui Song; Dongping Liao; Yiren Zhao; Kejiang Ye; ChengZhong Xu 001; Xitong Gao (CoRR, 2025)