9 citations · 18 across the 6 of their papers we have counts for
7 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…
Beyond Single Images: Retrieval Self-Augmented Unsupervised Camouflaged Object Detection
Ji Du, Xin Wang, Fangwei Hao +6
At the core of Camouflaged Object Detection (COD) lies segmenting objects from their highly similar surroundings. Previous efforts navigate this challenge primarily through image-l…
QVecOpt: An Efficient Storage and Computing Opti-mization Framework for Large-scale Quantum State Simulation
Mingyang Yu, Haorui Yang, Donglin Wang +4
In response to the challenges in large-scale quantum state simulation on classical computing platforms, including memory limits, frequent disk I/O, and high computational complexit…
Distributed Shared Layered Storage Quantum Simulator: A novel quantum simulation system for efficient scaling and cost optimization
Mingyang Yu, Haorui Yang, Donglin Wang +5
Quantum simulators are essential tools for developing and testing quantum algorithms. However, the high-frequency traversal characteristic of quantum simulators represents an unpre…
Efficient Star Distillation Attention Network for Lightweight Image Super-Resolution
Fangwei Hao, Ji Du, Desheng Kong +3
In recent years, the performance of lightweight Single-Image Super-Resolution (SISR) has been improved significantly with the application of Convolutional Neural Networks (CNNs) an…
Towards Context-aware Convolutional Network for Image Restoration
Fangwei Hao, Ji Du, Weiyun Liang +2
Image restoration (IR) is a long-standing task to recover a high-quality image from its corrupted observation. Recently, transformer-based algorithms and some attention-based convo…
Cross-Modal ASR Post-Processing System for Error Correction and Utterance Rejection
Jing Du, Shiliang Pu, Qinbo Dong +5
Although modern automatic speech recognition (ASR) systems can achieve high performance, they may produce errors that weaken readers' experience and do harm to downstream tasks. To…