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Found 32 papers, 14 papers with code
基于强负采样的词嵌入优化算法(Word Embedding Optimization Based on Hard Negative Sampling)
word2vec是自然语言处理领域重要的词嵌入算法之一, 为了解决随机负采样作为优化目标可能出现的样本贡献消失问题, 提出了可以应用在CBOW和Skip-gram框架上的以余弦距离为度量的强负采样方法:HNS-CBOW和HNS-SG。将原随机负采样过程拆解为两个步骤, 首先, 计算随机负样本与目标词的余弦距离, 然后, 再使用距离较近的强负样本更新参数。以英文维基百科数据作为实验语料, 在公开的语义-语法数据集上对优化算法的效果进行了定量分析, 实验表明, 优化后的词嵌入质量显著优于原方法。同时, 与GloVe等公开发布的预训练词向量相比, 可以在更小的语料库上获得更高的准确性。
Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin
Adapting vision-language models (VLMs) to downstream tasks with pseudolabels has gained increasing attention.
Multidimensional precipitation index prediction based on CNN-LSTM hybrid framework
This study proposes a multidimensional precipitation index prediction model based on a CNN- LSTM hybrid framework, aiming to improve the accuracy of precipitation forecasts.
From Code Generation to Software Testing: AI Copilot with Context-Based RAG
The rapid pace of large-scale software development places increasing demands on traditional testing methodologies, often leading to bottlenecks in efficiency, accuracy, and coverage.
TrafficKAN-GCN: Graph Convolutional-based Kolmogorov-Arnold Network for Traffic Flow Optimization
Urban traffic optimization is critical for improving transportation efficiency and alleviating congestion, particularly in large-scale dynamic networks.
Complementary Advantages: Exploiting Cross-Field Frequency Correlation for NIR-Assisted Image Denoising
The prior reveals the complementary correlation of NIR and RGB images in the frequency domain.
AnchorCrafter: Animate CyberAnchors Saling Your Products via Human-Object Interacting Video Generation
The automatic generation of anchor-style product promotion videos presents promising opportunities in online commerce, advertising, and consumer engagement.
Seismic Phase Picking
Seismic phase picking, which aims to determine the arrival time of P- and S-waves according to seismic waveforms, is fundamental to earthquake monitoring.
Contextual Augmented Multi-Model Programming (CAMP): A Hybrid Local-Cloud Copilot Framework
The advancements in cloud-based Large Languages Models (LLMs) have revolutionized AI-assisted programming.
Dual-branch PolSAR Image Classification Based on GraphMAE and Local Feature Extraction
Therefore, classifying PolSAR images with limited labels is a challenging task in remote sensing domain.
Global-Local Convolution with Spiking Neural Networks for Energy-efficient Keyword Spotting
Here, we take advantage of spiking neural networks' energy efficiency and propose an end-to-end lightweight KWS model.
MMBee: Live Streaming Gift-Sending Recommendations via Multi-Modal Fusion and Behaviour Expansion
To alleviate the sparsity issue of gifting behaviors, we present a novel Graph-guided Interest Expansion (GIE) approach that learns both user and streamer representations on large-scale gifting graphs with multi-modal attributes.
Achieving Resolution-Agnostic DNN-based Image Watermarking: A Novel Perspective of Implicit Neural Representation
Unlike previous methods, our method does not rely on the previous reduction process by directly watermarking the continuous signal instead of image pixels, thus achieving resolution-agnostic watermarking.
Fermi-Bose Machine achieves both generalization and adversarial robustness
Distinct from human cognitive processing, deep neural networks trained by backpropagation can be easily fooled by adversarial examples.
Detection of Opioid Users from Reddit Posts via an Attention-based Bidirectional Recurrent Neural Network
The opioid epidemic, referring to the growing hospitalizations and deaths because of overdose of opioid usage and addiction, has become a severe health problem in the United States.
Fusing Personal and Environmental Cues for Identification and Segmentation of First-Person Camera Wearers in Third-Person Views
As wearable cameras become more popular an important question emerges: how to identify camera wearers within the perspective of conventional static cameras.
Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives
We present Ego-Exo4D, a diverse, large-scale multimodal multiview video dataset and benchmark challenge.
Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization
Specifically, our RUAD can more effectively alleviate the feature sensitivity of the uplift model through two customized modules, including a feature selection module with joint multi-label modeling to identify a key subset from the input features and an adversarial feature desensitization module using adversarial training and soft interpolation operations to enhance the robustness of the model against this selected subset of features.
Understand Legal Documents with Contextualized Large Language Models
The growth of pending legal cases in populous countries, such as India, has become a major issue.
Label Information Enhanced Fraud Detection against Low Homophily in Graphs
Then, we combine the group aggregation and the learnable encodings into a Transformer encoder to capture the semantic information.
Whodunit? Learning to Contrast for Authorship Attribution
To the best of our knowledge, we are the first to integrate contrastive learning with pre-trained language model fine-tuning for authorship attribution.
Key-frame Guided Network for Thyroid Nodule Recognition using Ultrasound Videos
Ultrasound examination is widely used in the clinical diagnosis of thyroid nodules (benign/malignant).
UNITER-Based Situated Coreference Resolution with Rich Multimodal Input
Our model ranks second in the official evaluation on the object coreference resolution task with an F1 score of 73. 3% after model ensembling.
Ego4D: Around the World in 3,000 Hours of Egocentric Video
We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite.
Stepwise Goal-Driven Networks for Trajectory Prediction
We propose to predict the future trajectories of observed agents (e. g., pedestrians or vehicles) by estimating and using their goals at multiple time scales.
Ranked #1 on
Trajectory Prediction
on HEV-I
A Flexible Rolling Regression Framework for Time-Varying SIRD models: Application to COVID-19
The present paper introduces a data-driven framework for describing the time-varying nature of an SIRD model in the context of COVID-19.
Forecasting Black Sigatoka Infection Risks with Latent Neural ODEs
Black Sigatoka disease severely decreases global banana production, and climate change aggravates the problem by altering fungal species distributions.
Deep Tiered Image Segmentation For Detecting Internal Ice Layers in Radar Imagery
Understanding the structure of Earth's polar ice sheets is important for modeling how global warming will impact polar ice and, in turn, the Earth's climate.
Qudits and high-dimensional quantum computing
Qudit is a multi-level computational unit alternative to the conventional 2-level qubit.
Quantum Physics
Unsupervised Traffic Accident Detection in First-Person Videos
Recognizing abnormal events such as traffic violations and accidents in natural driving scenes is essential for successful autonomous driving and advanced driver assistance systems.
Ranked #1 on
Traffic Accident Detection
on A3D
Joint Person Segmentation and Identification in Synchronized First- and Third-person Videos
In this paper, we wish to solve two specific problems: (1) given two or more synchronized third-person videos of a scene, produce a pixel-level segmentation of each visible person and identify corresponding people across different views (i. e., determine who in camera A corresponds with whom in camera B), and (2) given one or more synchronized third-person videos as well as a first-person video taken by a mobile or wearable camera, segment and identify the camera wearer in the third-person videos.
