12 citations · 15 across the 5 of their papers we have counts for
6 papers
ERNIE 5.0 Technical Report
Haifeng Wang, Hua Wu, Tian Wu +432
In this report, we introduce ERNIE 5.0, a natively autoregressive foundation model desinged for unified multimodal understanding and generation across text, image, video, and audio…
Enhancing Automated Paper Reproduction via Prompt-Free Collaborative Agents
Zijie Lin, Qilin Cai, Liang Shen +1
Automated paper reproduction has emerged as a promising approach to accelerate scientific research, employing multi-step workflow frameworks to systematically convert academic pape…
Multimodal Chip Physical Design Engineer Assistant
Yun-Da Tsai, Chang-Yu Chao, Liang-Yeh Shen +7
Modern chip physical design relies heavily on Electronic Design Automation (EDA) tools, which often struggle to provide interpretable feedback or actionable guidance for improving…
Meta-PerSER: Few-Shot Listener Personalized Speech Emotion Recognition via Meta-learning
Liang-Yeh Shen, Shi-Xin Fang, Yi-Cheng Lin +2
This paper introduces Meta-PerSER, a novel meta-learning framework that personalizes Speech Emotion Recognition (SER) by adapting to each listener's unique way of interpreting emot…
MoESys: A Distributed and Efficient Mixture-of-Experts Training and Inference System for Internet Services
Dianhai Yu, Liang Shen, Hongxiang Hao +5
While modern internet services, such as chatbots, search engines, and online advertising, demand the use of large-scale deep neural networks (DNNs), distributed training and infere…
End-to-end Adaptive Distributed Training on PaddlePaddle
Yulong Ao, Zhihua Wu, Dianhai Yu +10
Distributed training has become a pervasive and effective approach for training a large neural network (NN) model with processing massive data. However, it is very challenging to s…