Zhongzhi Yu
Orcid: 0000-0002-9981-4981
According to our database1,
Zhongzhi Yu
authored at least 28 papers
between 2017 and 2024.
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Bibliography
2024
Model Tells You Where to Merge: Adaptive KV Cache Merging for LLMs on Long-Context Tasks.
CoRR, 2024
CoRR, 2024
EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning and Voting.
CoRR, 2024
AmoebaLLM: Constructing Any-Shape Large Language Models for Efficient and Instant Deployment.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Unified Compression and Adaptive Layer Voting.
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024
2023
EyeCoD: Eye Tracking System Acceleration via FlatCam-Based Algorithm and Hardware Co-Design.
IEEE Micro, 2023
Master-ASR: Achieving Multilingual Scalability and Low-Resource Adaptation in ASR with Modular Learning.
CoRR, 2023
Master-ASR: Achieving Multilingual Scalability and Low-Resource Adaptation in ASR with Modular Learning.
Proceedings of the International Conference on Machine Learning, 2023
GPT4AIGChip: Towards Next-Generation AI Accelerator Design Automation via Large Language Models.
Proceedings of the IEEE/ACM International Conference on Computer Aided Design, 2023
ViTCoD: Vision Transformer Acceleration via Dedicated Algorithm and Accelerator Co-Design.
Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2023
NetBooster: Empowering Tiny Deep Learning By Standing on the Shoulders of Deep Giants.
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023
Hint-Aug: Drawing Hints from Foundation Vision Transformers towards Boosted Few-shot Parameter-Efficient Tuning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
LDP: Learnable Dynamic Precision for Efficient Deep Neural Network Training and Inference.
CoRR, 2022
Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
EyeCoD: eye tracking system acceleration via flatcam-based algorithm & accelerator co-design.
Proceedings of the ISCA '22: The 49th Annual International Symposium on Computer Architecture, New York, New York, USA, June 18, 2022
MIA-Former: Efficient and Robust Vision Transformers via Multi-Grained Input-Adaptation.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
Identification of pediatric respiratory diseases using a fine-grained diagnosis system.
J. Biomed. Informatics, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
O-HAS: Optical Hardware Accelerator Search for Boosting Both Acceleration Performance and Development Speed.
Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2021
A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning.
Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021
InstantNet: Automated Generation and Deployment of Instantaneously Switchable-Precision Networks.
Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021
2020
Auto-Agent-Distiller: Towards Efficient Deep Reinforcement Learning Agents via Neural Architecture Search.
CoRR, 2020
2018
Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics, 2018
2017
Using OS Design Patterns to Provide Reliability and Security as-a-Service for VM-based Clouds.
Proceedings of the 13th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments, 2017