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Found 13 papers, 5 papers with code
PCQA: A Strong Baseline for AIGC Quality Assessment Based on Prompt Condition
It is essential to build an effective quality assessment framework to provide a quantifiable evaluation of different images or videos based on the AIGC technologies.
Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey
Recent breakthroughs in large language modeling have facilitated rigorous exploration of their application in diverse tasks related to tabular data modeling, such as prediction, tabular data synthesis, question answering, and table understanding.
Pruner: An Efficient Cross-Platform Tensor Compiler with Dual Awareness
Tensor program optimization on Deep Learning Accelerators (DLAs) is critical for efficient model deployment.
HR-MultiWOZ: A Task Oriented Dialogue (TOD) Dataset for HR LLM Agent
The data generation pipeline is transferable and can be easily adapted for labeled conversation data generation in other domains.
Defect Spectrum: A Granular Look of Large-Scale Defect Datasets with Rich Semantics
Defect inspection is paramount within the closed-loop manufacturing system.
Soft-tissue Driven Craniomaxillofacial Surgical Planning
Our framework consists of a bony planner network that estimates the bony movements required to achieve the desired facial outcome and a facial simulator network that can simulate the possible facial changes resulting from the estimated bony movement plans.
Causal Information Bottleneck Boosts Adversarial Robustness of Deep Neural Network
With the utilization of such a framework, the influence of non-robust features could be mitigated to strengthen the adversarial robustness.
Deep Learning-based Facial Appearance Simulation Driven by Surgically Planned Craniomaxillofacial Bony Movement
In this work, we propose an Attentive Correspondence assisted Movement Transformation network (ACMT-Net) to estimate the facial appearance by transforming the bony movement to facial soft tissue through a point-to-point attentive correspondence matrix.
Integrative Analysis for COVID-19 Patient Outcome Prediction
Management of high-risk patients with early intervention is a key to lower the fatality rate of COVID-19 pneumonia, as a majority of patients recover naturally.
Multi-organ Segmentation over Partially Labeled Datasets with Multi-scale Feature Abstraction
Shortage of fully annotated datasets has been a limiting factor in developing deep learning based image segmentation algorithms and the problem becomes more pronounced in multi-organ segmentation.
Unified Multi-scale Feature Abstraction for Medical Image Segmentation
Automatic medical image segmentation, an essential component of medical image analysis, plays an importantrole in computer-aided diagnosis.
Multi-class Active Learning: A Hybrid Informative and Representative Criterion Inspired Approach
Simultaneously, our proposed method makes full use of the label information, and the proposed active learning is designed based on multiple classes.
Towards Real-Time Advancement of Underwater Visual Quality with GAN
More specifically, an underwater index is investigated to describe underwater properties, and a loss function based on the underwater index is designed to train the critic branch for underwater noise suppression.
