:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Fu, Yonggan, Guo, Han, Li, Meng, Yang, Xin, Ding, Yining, Chandra, Vikas, Lin, Yingyan Celine
Format:	Preprint
Published:	2021
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2101.09868
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Auto-Agent-Distiller: Towards Efficient Deep Reinforcement Learning Agents via Neural Architecture Search
by: Fu, Yonggan, et al.
Published: (2020)

DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks
by: Fu, Yonggan, et al.
Published: (2022)

DNA: Differentiable Network-Accelerator Co-Search
by: Zhang, Yongan, et al.
Published: (2020)

ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks
by: You, Haoran, et al.
Published: (2022)

Early-Bird GCNs: Graph-Network Co-Optimization Towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Tickets
by: You, Haoran, et al.
Published: (2021)

Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators
by: Fu, Yonggan, et al.
Published: (2021)

A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning
by: Fu, Yonggan, et al.
Published: (2021)

2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency
by: Fu, Yonggan, et al.
Published: (2021)

DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference
by: Li, Chaojian, et al.
Published: (2021)

Drawing Early-Bird Tickets: Towards More Efficient Training of Deep Networks
by: You, Haoran, et al.
Published: (2019)

Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration
by: Yu, Zhongzhi, et al.
Published: (2024)

Robust Tickets Can Transfer Better: Drawing More Transferable Subnetworks in Transfer Learning
by: Fu, Yonggan, et al.
Published: (2023)

InstantNet: Automated Generation and Deployment of Instantaneously Switchable-Precision Networks
by: Fu, Yonggan, et al.
Published: (2021)

MG-Verilog: Multi-grained Dataset Towards Enhanced LLM-assisted Verilog Generation
by: Zhang, Yongan, et al.
Published: (2024)

Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks
by: Fu, Yonggan, et al.
Published: (2021)

AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks
by: Fu, Yonggan, et al.
Published: (2020)

Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing
by: Fu, Yonggan, et al.
Published: (2022)

HW-NAS-Bench:Hardware-Aware Neural Architecture Search Benchmark
by: Li, Chaojian, et al.
Published: (2021)

GPT4AIGChip: Towards Next-Generation AI Accelerator Design Automation via Large Language Models
by: Fu, Yonggan, et al.
Published: (2023)

Gen-NeRF: Efficient and Generalizable Neural Radiance Fields via Algorithm-Hardware Co-Design
by: Fu, Yonggan, et al.
Published: (2023)

AmoebaLLM: Constructing Any-Shape Large Language Models for Efficient and Instant Deployment
by: Fu, Yonggan, et al.
Published: (2024)

FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training
by: Fu, Yonggan, et al.
Published: (2020)

ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer
by: You, Haoran, et al.
Published: (2023)

Omni-Recon: Harnessing Image-based Rendering for General-Purpose Neural Radiance Fields
by: Fu, Yonggan, et al.
Published: (2024)

NeRFool: Uncovering the Vulnerability of Generalizable Neural Radiance Fields against Adversarial Perturbations
by: Fu, Yonggan, et al.
Published: (2023)

Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?
by: Fu, Yonggan, et al.
Published: (2022)

ERSAM: Neural Architecture Search For Energy-Efficient and Real-Time Social Ambiance Measurement
by: Li, Chaojian, et al.
Published: (2023)

Efficient-DLM: From Autoregressive to Diffusion Language Models, and Beyond in Speed
by: Fu, Yonggan, et al.
Published: (2025)

Self-Vocabularizing Training for Neural Machine Translation
by: Lin, Pin-Jie, et al.
Published: (2025)

CycleBNN: Cyclic Precision Training in Binary Neural Networks
by: Fontana, Federico, et al.
Published: (2024)

When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models
by: You, Haoran, et al.
Published: (2024)

LaCache: Ladder-Shaped KV Caching for Efficient Long-Context Modeling of Large Language Models
by: Shi, Dachuan, et al.
Published: (2025)

MixGCN: Scalable GCN Training by Mixture of Parallelism and Mixture of Accelerators
by: Wan, Cheng, et al.
Published: (2025)

Auto-CARD: Efficient and Robust Codec Avatar Driving for Real-time Mobile Telepresence
by: Fu, Yonggan, et al.
Published: (2023)

GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design
by: You, Haoran, et al.
Published: (2021)

ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization
by: You, Haoran, et al.
Published: (2024)

LongMamba: Enhancing Mamba's Long Context Capabilities via Training-Free Receptive Field Enlargement
by: Ye, Zhifan, et al.
Published: (2025)

$R^2$-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction
by: Du, Zhenbang, et al.
Published: (2026)

ShiftAddNet: A Hardware-Inspired Deep Network
by: You, Haoran, et al.
Published: (2020)

Scaling Laws of Graph Neural Networks for Atomistic Materials Modeling
by: Li, Chaojian, et al.
Published: (2025)