Pang, Ruoming

EfficientDet: Scalable and Efficient Object Detection

Tan, M., Pang, R., & Le, Q. V. (2019) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 9,841

Searching for MobileNetV3

Howard, A., Sandler, M., Chen, B., Wang, W., Chen, L.-C., Tan, M., Chu, G., Vasudevan, V., Zhu, Y., Pang, R., et al. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 9,708

MnasNet: Platform-Aware Neural Architecture Search for Mobile

Tan, M., Chen, B., Pang, R., Vasudevan, V., Sandler, M., Howard, A., & Le, Q. V. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsMachine Learning and Data Classification

Cited by 3,416

Conformer: Convolution-augmented Transformer for Speech Recognition

Gulati, A., Qin, J., Chiu, C.-C., Parmar, N., Zhang, Y., Yu, J., Han, W., Wang, S., Zhang, Z., Wu, Y., et al. (2020) · Interspeech 2020

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 3,150

Conformer: Convolution-augmented Transformer for Speech Recognition

Gulati, A., Qin, J., Chiu, C.-C., Parmar, N., Zhang, Y., Yu, J., Han, W., Wang, S., Zhang, Z., Wu, Y., et al. (2020) · arXiv

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 3,150

Natural TTS Synthesis by Conditioning Wavenet on MEL Spectrogram Predictions

Shen, J., Pang, R., Weiss, R. J., Schuster, M., Jaitly, N., Yang, Z., Chen, Z., Zhang, Y., Wang, Y., Skerrv-Ryan, R., et al. (2018) · 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 2,791

Streaming End-to-end Speech Recognition for Mobile Devices

He, Y., Sainath, T. N., Prabhavalkar, R., McGraw, I., Alvarez, R., Zhao, D., Rybach, D., Kannan, A., Wu, Y., Pang, R., et al. (2019) · ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 601

Transfer learning from speaker verification to multispeaker text-to-speech synthesis

Jia, Y., Zhang, Y., Weiss, R. J., Wang, Q., Shen, J., Ren, F., Chen, Z., Nguyen, P., Pang, R., Moreno, I. L., et al. (2018) · arXiv

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 519

w2v-BERT: Combining Contrastive Learning and Masked Language Modeling for Self-Supervised Speech Pre-Training

Chung, Y.-A., Zhang, Y., Han, W., Chiu, C.-C., Qin, J., Pang, R., & Wu, Y. (2021) · 2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 293

BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition

Zhang, Y., Park, D. S., Han, W., Qin, J., Gulati, A., Shor, J., Jansen, A., Xu, Y., Huang, Y., Wang, S., et al. (2022) · IEEE Journal of Selected Topics in Signal Processing

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 161

ToolSandbox: A Stateful, Conversational, Interactive Evaluation Benchmark for LLM Tool Use Capabilities

Lu, J., Holleis, T., Zhang, Y., Aumayer, B., Nan, F., Bai, F., Ma, S., Ma, S., Li, M., Yin, G., et al. (2024) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 2

MMAU: A Holistic Benchmark of Agent Capabilities Across Diverse Domains

Yin, G., Bai, H., Ma, S., Nan, F., Sun, Y., Xu, Z., Ma, S., Lu, J., Kong, X., Zhang, A., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1

RATTENTION: Towards the Minimal Sliding Window Size in Local-Global Attention Models

Wang, B., Lan, C., Wang, C., & Pang, R. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0