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Found 9 papers, 3 papers with code
Exploring Label Hierarchy in a Generative Way for Hierarchical Text Classification
Hierarchical Text Classification (HTC), which aims to predict text labels organized in hierarchical space, is a significant task lacking in investigation in natural language processing.
RangeLDM: Fast Realistic LiDAR Point Cloud Generation
Autonomous driving demands high-quality LiDAR data, yet the cost of physical LiDAR sensors presents a significant scaling-up challenge.
InvariantOODG: Learning Invariant Features of Point Clouds for Out-of-Distribution Generalization
The convenience of 3D sensors has led to an increase in the use of 3D point clouds in various applications.
A unified consensus-based parallel ADMM algorithm for high-dimensional regression with combined regularizations
The parallel alternating direction method of multipliers (ADMM) algorithm is widely recognized for its effectiveness in handling large-scale datasets stored in a distributed manner, making it a popular choice for solving statistical learning models.
Unsupervised Manga Character Re-identification via Face-body and Spatial-temporal Associated Clustering
In the past few years, there has been a dramatic growth in e-manga (electronic Japanese-style comics).
Improving Stack Overflow question title generation with copying enhanced CodeBERT model and bi-modal information
However, only using the code snippets in the question body cannot provide sufficient information for title generation, and LSTMs cannot capture the long-range dependencies between tokens.
Hierarchy-Aware T5 with Path-Adaptive Mask Mechanism for Hierarchical Text Classification
Hierarchical Text Classification (HTC), which aims to predict text labels organized in hierarchical space, is a significant task lacking in investigation in natural language processing.
HyGCN: A GCN Accelerator with Hybrid Architecture
In this work, we first characterize the hybrid execution patterns of GCNs on Intel Xeon CPU.
Distributed, Parallel, and Cluster Computing
Unsupervised monocular stereo matching
In this paper, Based on the experimental results that the stereo matching models outperforms monocular depth estimation models under the same unsupervised depth estimation model, we proposed an unsupervised monocular vision stereo matching method.
