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09/19/2023
FoleyGen: Visually-Guided Audio Generation
Recent advancements in audio generation have been spurred by the evoluti...
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09/15/2023
Stack-and-Delay: a new codebook pattern for music generation
In language modeling based music generation, a generated waveform is rep...
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09/05/2023
TODM: Train Once Deploy Many Efficient Supernet-Based RNN-T Compression For On-device ASR Models
Automatic Speech Recognition (ASR) models need to be optimized for speci...
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07/01/2023
Revisiting Sample Size Determination in Natural Language Understanding
Knowing exactly how many data points need to be labeled to achieve a cer...
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06/08/2023
Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts
Weight-sharing supernet has become a vital component for performance est...
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05/29/2023
LLM-QAT: Data-Free Quantization Aware Training for Large Language Models
Several post-training quantization methods have been applied to large la...
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12/12/2022
PathFusion: Path-consistent Lidar-Camera Deep Feature Fusion
Fusing camera with LiDAR is a promising technique to improve the accurac...
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12/07/2022
SDRM3: A Dynamic Scheduler for Dynamic Real-time Multi-model ML Workloads
Emerging real-time multi-model ML (RTMM) workloads such as AR/VR and dro...
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12/04/2022
Fast Point Cloud Generation with Straight Flows
Diffusion models have emerged as a powerful tool for point cloud generat...
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11/16/2022
XRBench: An Extended Reality (XR) Machine Learning Benchmark Suite for the Metaverse
Real-time multi-model multi-task (MMMT) workloads, a new form of deep le...
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11/09/2022
LiCo-Net: Linearized Convolution Network for Hardware-efficient Keyword Spotting
This paper proposes a hardware-efficient architecture, Linearized Convol...
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06/02/2022
DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks
Efficient deep neural network (DNN) models equipped with compact operato...
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03/29/2022
Streaming parallel transducer beam search with fast-slow cascaded encoders
Streaming ASR with strict latency constraints is required in many speech...
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11/02/2021
Low-Rank+Sparse Tensor Compression for Neural Networks
Low-rank tensor compression has been proposed as a promising approach to...
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11/01/2021
HRViT: Multi-Scale High-Resolution Vision Transformer
Vision transformers (ViTs) have attracted much attention for their super...
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10/15/2021
Omni-sparsity DNN: Fast Sparsity Optimization for On-Device Streaming E2E ASR via Supernet
From wearables to powerful smart devices, modern automatic speech recogn...
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07/09/2021
Noisy Training Improves E2E ASR for the Edge
Automatic speech recognition (ASR) has become increasingly ubiquitous on...
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06/16/2021
Collaborative Training of Acoustic Encoders for Speech Recognition
On-device speech recognition requires training models of different sizes...
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04/26/2021
Improve Vision Transformers Training by Suppressing Over-smoothing
Introducing the transformer structure into computer vision tasks holds t...
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03/02/2021
Feature-Align Network and Knowledge Distillation for Efficient Denoising
Deep learning-based RAW image denoising is a quintessential problem in i...
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03/02/2021
Mind Mappings: Enabling Efficient Algorithm-Accelerator Mapping Space Search
Modern day computing increasingly relies on specialization to satiate gr...
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02/23/2021
Memory-efficient Speech Recognition on Smart Devices
Recurrent transducer models have emerged as a promising solution for spe...
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02/16/2021
AlphaNet: Improved Training of Supernet with Alpha-Divergence
Weight-sharing neural architecture search (NAS) is an effective techniqu...
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01/25/2021
CPT: Efficient Deep Neural Network Training via Cyclic Precision
Low-precision deep neural network (DNN) training has gained tremendous a...
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12/03/2020
EVRNet: Efficient Video Restoration on Edge Devices
Video transmission applications (e.g., conferencing) are gaining momentu...
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11/30/2020
ScaleNAS: One-Shot Learning of Scale-Aware Representations for Visual Recognition
Scale variance among different sizes of body parts and objects is a chal...
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11/25/2020
Can Temporal Information Help with Contrastive Self-Supervised Learning?
Leveraging temporal information has been regarded as essential for devel...
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11/23/2020
KeepAugment: A Simple Information-Preserving Data Augmentation Approach
Data augmentation (DA) is an essential technique for training state-of-t...
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11/18/2020
AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling
Neural architecture search (NAS) has shown great promise designing state...
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10/28/2020
DNA: Differentiable Network-Accelerator Co-Search
Powerful yet complex deep neural networks (DNNs) have fueled a booming d...
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08/22/2020
One Weight Bitwidth to Rule Them All
Weight quantization for deep ConvNets has shown promising results for ap...
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07/08/2020
NASGEM: Neural Architecture Search via Graph Embedding Method
Neural Architecture Search (NAS) automates and prospers the design of ne...
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02/13/2020
Improving Efficiency in Neural Network Accelerator Using Operands Hamming Distance optimization
Neural network accelerator is a key enabler for the on-device AI inferen...
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02/10/2020
Co-Exploration of Neural Architectures and Heterogeneous ASIC Accelerator Designs Targeting Multiple Tasks
Neural Architecture Search (NAS) has demonstrated its power on various A...
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12/30/2019
RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing
Personalized recommendation systems leverage deep learning models and ac...
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10/07/2019
Energy-Aware Neural Architecture Optimization with Fast Splitting Steepest Descent
Designing energy-efficient networks is of critical importance for enabli...
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09/13/2019
HERALD: Optimizing Heterogeneous DNN Accelerators for Edge Devices
Recent advances in deep neural networks (DNNs) have made DNNs the backbo...
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06/02/2018
Federated Learning with Non-IID Data
Federated learning enables resource-constrained edge compute devices, su...
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01/19/2018
CMSIS-NN: Efficient Neural Network Kernels for Arm Cortex-M CPUs
Deep Neural Networks are becoming increasingly popular in always-on IoT ...
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01/12/2018
Not All Ops Are Created Equal!
Efficient and compact neural network models are essential for enabling t...
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12/05/2017
Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Networks
Hardware acceleration of Deep Neural Networks (DNNs) aims to tame their ...
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11/20/2017
Hello Edge: Keyword Spotting on Microcontrollers
Keyword spotting (KWS) is a critical component for enabling speech based...
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03/08/2017