Saved in:
| Main Authors: | Ji, Yang, Sun, Ying, Zhu, Hengshu |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.12978 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Job Market Cheat Codes: Prototyping Salary Prediction and Job Grouping with Synthetic Job Listings
by: Alsheyab, Abdel Rahman, et al.
Published: (2025)
by: Alsheyab, Abdel Rahman, et al.
Published: (2025)
Labor Migration Modeling through Large-scale Job Query Data
by: Guo, Zhuoning, et al.
Published: (2024)
by: Guo, Zhuoning, et al.
Published: (2024)
Job-SDF: A Multi-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking
by: Chen, Xi, et al.
Published: (2024)
by: Chen, Xi, et al.
Published: (2024)
A Comprehensive Survey on Self-Interpretable Neural Networks
by: Ji, Yang, et al.
Published: (2025)
by: Ji, Yang, et al.
Published: (2025)
Adapting Job Recommendations to User Preference Drift with Behavioral-Semantic Fusion Learning
by: Han, Xiao, et al.
Published: (2024)
by: Han, Xiao, et al.
Published: (2024)
Make Large Language Model a Better Ranker
by: Chao, Wen-Shuo, et al.
Published: (2024)
by: Chao, Wen-Shuo, et al.
Published: (2024)
A Cross-View Hierarchical Graph Learning Hypernetwork for Skill Demand-Supply Joint Prediction
by: Chao, Wenshuo, et al.
Published: (2024)
by: Chao, Wenshuo, et al.
Published: (2024)
Predefined Prototypes for Intra-Class Separation and Disentanglement
by: Almudévar, Antonio, et al.
Published: (2024)
by: Almudévar, Antonio, et al.
Published: (2024)
The Value of Graph-based Encoding in NBA Salary Prediction
by: Su, Junhao, et al.
Published: (2026)
by: Su, Junhao, et al.
Published: (2026)
Dual-Prototype Disentanglement: A Context-Aware Enhancement Framework for Time Series Forecasting
by: Yang, Haonan, et al.
Published: (2026)
by: Yang, Haonan, et al.
Published: (2026)
Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning
by: Huang, Zheng, et al.
Published: (2024)
by: Huang, Zheng, et al.
Published: (2024)
Online MDP with Transition Prototypes: A Robust Adaptive Approach
by: Sun, Shuo, et al.
Published: (2024)
by: Sun, Shuo, et al.
Published: (2024)
A Data-Driven Approach to Enhancing Gravity Models for Trip Demand Prediction
by: Acharya, Kamal, et al.
Published: (2025)
by: Acharya, Kamal, et al.
Published: (2025)
COMIX: Compositional Explanations using Prototypes
by: Sivaprasad, Sarath, et al.
Published: (2025)
by: Sivaprasad, Sarath, et al.
Published: (2025)
Convergence-aware Clustered Federated Graph Learning Framework for Collaborative Inter-company Labor Market Forecasting
by: Guo, Zhuoning, et al.
Published: (2024)
by: Guo, Zhuoning, et al.
Published: (2024)
Towards Efficient Resume Understanding: A Multi-Granularity Multi-Modal Pre-Training Approach
by: Jiang, Feihu, et al.
Published: (2024)
by: Jiang, Feihu, et al.
Published: (2024)
Energy Score-Guided Neural Gaussian Mixture Model for Predictive Uncertainty Quantification
by: Yang, Yang, et al.
Published: (2026)
by: Yang, Yang, et al.
Published: (2026)
Enhance the Safety in Reinforcement Learning by ADRC Lagrangian Methods
by: Zhang, Mingxu, et al.
Published: (2026)
by: Zhang, Mingxu, et al.
Published: (2026)
Disentangled Representation via Variational AutoEncoder for Continuous Treatment Effect Estimation
by: Cui, Ruijing, et al.
Published: (2024)
by: Cui, Ruijing, et al.
Published: (2024)
E-ICL: Enhancing Fine-Grained Emotion Recognition through the Lens of Prototype Theory
by: Ren, Zhaochun, et al.
Published: (2024)
by: Ren, Zhaochun, et al.
Published: (2024)
A Predictive Approach To Enhance Time-Series Forecasting
by: Gunasekaran, Skye, et al.
Published: (2024)
by: Gunasekaran, Skye, et al.
Published: (2024)
Learning Domain- and Class-Disentangled Prototypes for Domain-Generalized EEG Emotion Recognition
by: Li, Guangli, et al.
Published: (2025)
by: Li, Guangli, et al.
Published: (2025)
Disentangling Neural Disjunctive Normal Form Models
by: Baugh, Kexin Gu, et al.
Published: (2025)
by: Baugh, Kexin Gu, et al.
Published: (2025)
Bias of Stochastic Gradient Descent or the Architecture: Disentangling the Effects of Overparameterization of Neural Networks
by: Peleg, Amit, et al.
Published: (2024)
by: Peleg, Amit, et al.
Published: (2024)
ReliCD: A Reliable Cognitive Diagnosis Framework with Confidence Awareness
by: Zhang, Yunfei, et al.
Published: (2023)
by: Zhang, Yunfei, et al.
Published: (2023)
Enhancing Predictive Capabilities in Data-Driven Dynamical Modeling with Automatic Differentiation: Koopman and Neural ODE Approaches
by: Constante-Amores, C. Ricardo, et al.
Published: (2023)
by: Constante-Amores, C. Ricardo, et al.
Published: (2023)
Fusion Matrix Prompt Enhanced Self-Attention Spatial-Temporal Interactive Traffic Forecasting Framework
by: Liu, Mu, et al.
Published: (2024)
by: Liu, Mu, et al.
Published: (2024)
JobFormer: Skill-Aware Job Recommendation with Semantic-Enhanced Transformer
by: Guan, Zhihao, et al.
Published: (2024)
by: Guan, Zhihao, et al.
Published: (2024)
Decision Transformer for Enhancing Neural Local Search on the Job Shop Scheduling Problem
by: de Puiseau, Constantin Waubert, et al.
Published: (2024)
by: de Puiseau, Constantin Waubert, et al.
Published: (2024)
Enhancing Explainability in Solar Energetic Particle Event Prediction: A Global Feature Mapping Approach
by: Ji, Anli, et al.
Published: (2025)
by: Ji, Anli, et al.
Published: (2025)
ProtoEHR: Hierarchical Prototype Learning for EHR-based Healthcare Predictions
by: Cai, Zi, et al.
Published: (2025)
by: Cai, Zi, et al.
Published: (2025)
DISCO: A Hierarchical Disentangled Cognitive Diagnosis Framework for Interpretable Job Recommendation
by: Yu, Xiaoshan, et al.
Published: (2024)
by: Yu, Xiaoshan, et al.
Published: (2024)
GeoPTH: A Lightweight Approach to Category-Based Trajectory Retrieval via Geometric Prototype Trajectory Hashing
by: Xu, Yang, et al.
Published: (2025)
by: Xu, Yang, et al.
Published: (2025)
Comprehensive Evaluation of Prototype Neural Networks
by: Schlinge, Philipp, et al.
Published: (2025)
by: Schlinge, Philipp, et al.
Published: (2025)
A Doubly Robust Machine Learning Approach for Disentangling Treatment Effect Heterogeneity with Functional Outcomes
by: Salmaso, Filippo, et al.
Published: (2026)
by: Salmaso, Filippo, et al.
Published: (2026)
Unsupervised Graph Neural Architecture Search with Disentangled Self-supervision
by: Zhang, Zeyang, et al.
Published: (2024)
by: Zhang, Zeyang, et al.
Published: (2024)
A Deep Positive-Negative Prototype Approach to Integrated Prototypical Discriminative Learning
by: Zarei-Sabzevar, Ramin, et al.
Published: (2025)
by: Zarei-Sabzevar, Ramin, et al.
Published: (2025)
Out-of-Distribution Generalized Dynamic Graph Neural Network with Disentangled Intervention and Invariance Promotion
by: Zhang, Zeyang, et al.
Published: (2023)
by: Zhang, Zeyang, et al.
Published: (2023)
Variational Approach for Job Shop Scheduling
by: Oh, Seung Heon, et al.
Published: (2026)
by: Oh, Seung Heon, et al.
Published: (2026)
Disentangling the Causes of Plasticity Loss in Neural Networks
by: Lyle, Clare, et al.
Published: (2024)
by: Lyle, Clare, et al.
Published: (2024)
Similar Items
-
Job Market Cheat Codes: Prototyping Salary Prediction and Job Grouping with Synthetic Job Listings
by: Alsheyab, Abdel Rahman, et al.
Published: (2025) -
Labor Migration Modeling through Large-scale Job Query Data
by: Guo, Zhuoning, et al.
Published: (2024) -
Job-SDF: A Multi-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking
by: Chen, Xi, et al.
Published: (2024) -
A Comprehensive Survey on Self-Interpretable Neural Networks
by: Ji, Yang, et al.
Published: (2025) -
Adapting Job Recommendations to User Preference Drift with Behavioral-Semantic Fusion Learning
by: Han, Xiao, et al.
Published: (2024)