multi-source learning

Hierarchical Dataset Selection for High-Quality Data Sharing AAAI 2026 Conditional Generative Learning from Invariant Representations in Multi-Source: Robustness and Efficiency AISTATS 2025 Cross-Document Event-Keyed Summarization ACL 2025 DAEA: Enhancing Entity Alignment in Real-World Knowledge Graphs Through Multi-Source Domain Adaptation COLING 2025 FDS: Feedback-Guided Domain Synthesis with Multi-Source Conditional Diffusion Models for Domain Generalization WACV 2025 MVP: Multi-source Voice Pathology detection Interspeech 2025 A New Multi-Source Light Detection Benchmark and Semi-Supervised Focal Light Detection NeurIPS 2024 A Transfer Approach Using Graph Neural Networks in Deep Reinforcement Learning AAAI 2024 DA-Net: A Disentangled and Adaptive Network for Multi-Source Cross-Lingual Transfer Learning AAAI 2024 Feature Structure Matching for Multi-source Sentiment Analysis with Efficient Adaptive Tuning COLING 2024 Linear Regression using Heterogeneous Data Batches NeurIPS 2024 Multi-Source Collaborative Gradient Discrepancy Minimization for Federated Domain Generalization AAAI 2024 Multi-Source Text Classification for Multilingual Sentence Encoder with Machine Translation NAACL 2024 Style Adaptation and Uncertainty Estimation for Multi-Source Blended-Target Domain Adaptation NeurIPS 2024 Tell me what I need to know: Exploring LLM-based (Personalized) Abstractive Multi-Source Meeting Summarization EMNLP 2024 Example-based Hypernetworks for Multi-source Adaptation to Unseen Domains EMNLP 2023 Investigating Multi-source Active Learning for Natural Language Inference EACL 2023 Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation NeurIPS 2023 Multi-source Learning via Completion of Block-wise Overlapping Noisy Matrices JMLR 2023 MetaTeacher: Coordinating Multi-Model Domain Adaptation for Medical Image Classification NeurIPS 2022 Robust Direct Learning for Causal Data Fusion ACML 2022 Textual Entailment for Event Argument Extraction: Zero- and Few-Shot with Multi-Source Learning NAACL 2022 An Empirical Study on Multiple Information Sources for Zero-Shot Fine-Grained Entity Typing EMNLP 2021 BERTifying the Hidden Markov Model for Multi-Source Weakly Supervised Named Entity Recognition ACL 2021 Boosting with Multiple Sources NeurIPS 2021