Yiren Zhao

CoRR, February, 2025

2024

AI models collapse when trained on recursively generated data.

[BibT_eX]

[DOI]

Nat., July, 2024

Refining Salience-Aware Sparse Fine-Tuning Strategies for Language Models.

[BibT_eX]

[DOI]

CoRR, 2024

Hardware and Software Platform Inference.

[BibT_eX]

[DOI]

CoRR, 2024

Absorb & Escape: Overcoming Single Model Limitations in Generating Genomic Sequences.

[BibT_eX]

[DOI]

Guoxuan Xia

Akashaditya Das

Guy-Bart Stan

CoRR, 2024

Scaling Laws for Mixed quantization in Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2024

QERA: an Analytical Framework for Quantization Error Reconstruction.

[BibT_eX]

[DOI]

Jeffrey T. H. Wong

Can Xiao

CoRR, 2024

Optimised Grouped-Query Attention Mechanism for Transformers.

[BibT_eX]

[DOI]

CoRR, 2024

Unlocking the Global Synergies in Low-Rank Adapters.

[BibT_eX]

[DOI]

CoRR, 2024

Δ-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers.

[BibT_eX]

[DOI]

Tao Chen

CoRR, 2024

Locking Machine Learning Models into Hardware.

[BibT_eX]

[DOI]

CoRR, 2024

Enhancing Real-World Complex Network Representations with Hyperedge Augmentation.

[BibT_eX]

[DOI]

CoRR, 2024

Architectural Neural Backdoors from First Principles.

[BibT_eX]

[DOI]

CoRR, 2024

DiscDiff: Latent Diffusion Model for DNA Sequence Generation.

[BibT_eX]

[DOI]

CoRR, 2024

Verification and Fault Injection Platform Based on MTB Stimulus Generation Method for L2 Deep Market Quote Decoder.

[BibT_eX]

[DOI]

IEEE Access, 2024

ImpNet: Imperceptible and blackbox-undetectable backdoors in compiled neural networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2024

GV-Rep: A Large-Scale Dataset for Genetic Variant Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Absorb & Escape: Overcoming Single Model Limitations in Generating Heterogeneous Genomic Sequences.

[BibT_eX]

[DOI]

Guoxuan Xia

Akashaditya Das

Guy-Bart Stan

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

LQER: Low-Rank Quantization Error Reconstruction for LLMs.

[BibT_eX]

[DOI]

George Anthony Constantinides

Alexander Montgomerie-Corcoran

Proceedings of the Forty-first International Conference on Machine Learning, 2024

HASS: Hardware-Aware Sparsity Search for Dataflow DNN Accelerator.

[BibT_eX]

[DOI]

Proceedings of the 34th International Conference on Field-Programmable Logic and Applications, 2024

Enhancing Node Representations for Real-World Complex Networks with Topological Augmentation.

[BibT_eX]

[DOI]

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023

Latent Diffusion Model for DNA Sequence Generation.

[BibT_eX]

[DOI]

Tim August B. Huygelen

CoRR, 2023

LLM4DV: Using Large Language Models for Hardware Test Stimuli Generation.

[BibT_eX]

[DOI]

CoRR, 2023

Fast Prototyping Next-Generation Accelerators for New ML Models using MASE: ML Accelerator System Exploration.

[BibT_eX]

[DOI]

Alexander Montgomerie-Corcoran

Zhewen Yu

Can Xiao

CoRR, 2023

Genomic Interpreter: A Hierarchical Genomic Deep Neural Network with 1D Shifted Window Transformer.

[BibT_eX]

[DOI]

Akashaditya Das

Guy-Bart Stan

CoRR, 2023

Hybrid Graph: A Unified Graph Representation with Datasets and Benchmarks for Complex Graphs.

[BibT_eX]

[DOI]

CoRR, 2023

The Curse of Recursion: Training on Generated Data Makes Models Forget.

[BibT_eX]

[DOI]

CoRR, 2023

Task-Agnostic Graph Neural Network Evaluation via Adversarial Collaboration.

[BibT_eX]

[DOI]

CoRR, 2023

FlexWAN: Software Hardware Co-design for Cost-Effective and Resilient Optical Backbones.

[BibT_eX]

[DOI]

Proceedings of the ACM SIGCOMM 2023 Conference, 2023

MiliPoint: A Point Cloud Dataset for mmWave Radar.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Will More Expressive Graph Neural Networks Do Better on Generative Tasks?

[BibT_eX]

[DOI]

Proceedings of the Learning on Graphs Conference, 27-30 November 2023, Virtual Event., 2023

Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM Inference?

[BibT_eX]

[DOI]

Ilia Shumailov

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Dynamic Stashing Quantization for Efficient Transformer Training.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Adaptive Channel Sparsity for Federated Learning under System Heterogeneity.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Architectural Backdoors in Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Revisiting Structured Dropout.

[BibT_eX]

[DOI]

Proceedings of the Asian Conference on Machine Learning, 2023

Revisiting Automated Prompting: Are We Actually Doing Better?

[BibT_eX]

[DOI]

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

2022

Flareon: Stealthy any2any Backdoor Injection via Poisoned Augmentation.

[BibT_eX]

[DOI]

CoRR, 2022

DARTFormer: Finding The Best Type Of Attention.

[BibT_eX]

[DOI]

CoRR, 2022

Wide Attention Is The Way Forward For Transformers.

[BibT_eX]

[DOI]

CoRR, 2022

ImpNet: Imperceptible and blackbox-undetectable backdoors in compiled neural networks.

[BibT_eX]

[DOI]

CoRR, 2022

Augmentation Backdoors.

[BibT_eX]

[DOI]

CoRR, 2022

Efficient Adversarial Training With Data Pruning.

[BibT_eX]

[DOI]

CoRR, 2022

Model Architecture Adaption for Bayesian Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2022

Rapid Model Architecture Adaption for Meta-Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning.

[BibT_eX]

[DOI]

Robert Hönig

Robert D. Mullins

Proceedings of the International Conference on Machine Learning, 2022

2021

Manipulating SGD with Data Ordering Attacks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Markpainting: Adversarial Machine Learning meets Inpainting.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Sponge Examples: Energy-Latency Attacks on Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE European Symposium on Security and Privacy, 2021

2020

Nudge Attacks on Point-Cloud DNNs.

[BibT_eX]

[DOI]

CoRR, 2020

Learned Low Precision Graph Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2020

Probabilistic Dual Network Architecture Search on Graphs.

[BibT_eX]

[DOI]

CoRR, 2020

Pay Attention to Features, Transfer Learn Faster CNNs.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Blackbox Attacks on Reinforcement Learning Agents Using Approximated Temporal Information.

[BibT_eX]

[DOI]

Proceedings of the 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, 2020

Towards Certifiable Adversarial Sample Detection.

[BibT_eX]

[DOI]

Proceedings of the AISec@CCS 2020: Proceedings of the 13th ACM Workshop on Artificial Intelligence and Security, 2020

2019

Efficient and Effective Quantization for Sparse DNNs.

[BibT_eX]

[DOI]

CoRR, 2019

Sitatapatra: Blocking the Transfer of Adversarial Samples.

[BibT_eX]

[DOI]

CoRR, 2019

Focused Quantization for Sparse CNNs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

To Compress Or Not To Compress: Understanding The Interactions Between Adversarial Attacks And Neural Network Compression.

[BibT_eX]

[DOI]

Proceedings of the Second Conference on Machine Learning and Systems, SysML 2019, 2019

Characterizing Sources of Ineffectual Computations in Deep Learning Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2019

Dynamic Channel Pruning: Feature Boosting and Suppression.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Automatic Generation of Multi-Precision Multi-Arithmetic CNN Accelerators for FPGAs.

[BibT_eX]

[DOI]

Cheng-Zhong Xu

Proceedings of the International Conference on Field-Programmable Technology, 2019

2018

The Taboo Trap: Behavioural Detection of Adversarial Samples.

[BibT_eX]

[DOI]

CoRR, 2018

Mayo: A Framework for Auto-generating Hardware Friendly Deep Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 2nd International Workshop on Embedded and Mobile Deep Learning, 2018

Redundancy-Reduced MobileNet Acceleration on Reconfigurable Logic for ImageNet Classification.

[BibT_eX]

[DOI]

Philip Heng Wai Leong

Peter Y. K. Cheung

Proceedings of the Applied Reconfigurable Computing. Architectures, Tools, and Applications, 2018

2016

An efficient implementation of online arithmetic.

[BibT_eX]

[DOI]

John Wickerson