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Embedding Learning

3751 directly classified papers

Papers per year

Papers

UWBa at SemEval-2025 Task 7: Multilingual and Crosslingual Fact-Checked Claim Retrieval SEMEVAL 2025
Beyond the Average Reader: the Reader Embedding Approach ACL 2025
Croppable Knowledge Graph Embedding ACL 2025
TreeRAG: Unleashing the Power of Hierarchical Storage for Enhanced Knowledge Retrieval in Long Documents ACL 2025
Latent Space Imaging CVPR 2025
Omni-ID: Holistic Identity Representation Designed for Generative Tasks CVPR 2025
CoRe: Context-Regularized Text Embedding Learning for Text-to-Image Personalization AAAI 2025
Maximal Matching Matters: Preventing Representation Collapse for Robust Cross-Modal Retrieval ACL 2025
Evaluating Design Decisions for Dual Encoder-based Entity Disambiguation ACL 2025
Group, Embed and Reason: A Hybrid LLM and Embedding Framework for Semantic Attribute Alignment EMNLP 2025
NAT: Learning to Attack Neurons for Enhanced Adversarial Transferability WACV 2025
When Annotators Disagree, Topology Explains: Mapper, a Topological Tool for Exploring Text Embedding Geometry and Ambiguity EMNLP 2025
Speech Vecalign: an Embedding-based Method for Aligning Parallel Speech Documents EMNLP 2025
Towards Visual Localization Interoperability: Cross-Feature for Collaborative Visual Localization and Mapping ICCV 2025
Seeing Through Words, Speaking Through Pixels: Deep Representational Alignment Between Vision and Language Models EMNLP 2025
Towards Ancient Meroitic Decipherment: A Computational Approach NAACL 2025
Generalized Embedding Models for Industry 4.0 Applications EMNLP 2025
Knowledge Graph Completion with Relation-Aware Anchor Enhancement AAAI 2025
Mind the Gap: Gender-based Differences in Occupational Embeddings ACL 2025
GLoCIM: Global-view Long Chain Interest Modeling for news recommendation COLING 2025
E-Gen: Leveraging E-Graphs to Improve Continuous Representations of Symbolic Expressions NAACL 2025
Retrieval of Temporal Event Sequences from Textual Descriptions NAACL 2025
Multi-word Measures: Modeling Semantic Change in Compound Nouns ACL 2025
Following the Autoregressive Nature of LLM Embeddings via Compression and Alignment EMNLP 2025
The Russian-focused embedders’ exploration: ruMTEB benchmark and Russian embedding model design NAACL 2025