Overview

Sentence embeddings represent whole sentences as vectors so systems can compare meaning, retrieve relevant text, group examples, or support classification. Common approaches use contrastive learning on paraphrases, natural language inference pairs, or translated parallel text, alongside distillation and different pooling methods to build or adapt encoders. Models are evaluated on semantic textual similarity, retrieval, inference, and classification benchmarks, with multilingual and domain-specific tests revealing that strong average scores do not guarantee performance in every language or task. A central tension is that single-vector similarity is efficient, but subtle meaning comparisons can require interactions between sentence pairs; robustness, interpretability, and reliable evaluation remain open challenges.

Latest papers

CardsList

35 papers3 papers in the last four weeks, level with the four weeks before. 0.0% of all new papers.

  1. TEMPS: Temporal Sentence Embeddings for Temporal Information Retrieval

    Sep 23, 2026Mourad Hassani, Julien Romero, Amel Bouzeghoub +1Sentence EmbeddingsTemporal IR

  2. Evaluating Multilingual Sentence Embeddings for Translation Error Detection:An English--Greek Contrastive Study

    Aug 28, 2026Eleftherios Kalogeros, Athanasios Ntalakas, Manolis Gergatsoulis +2MT EvaluationSentence Embeddings

  3. KinyaEmbed: Contrastive Sentence Embeddings for Kinyarwanda via Multi-Stage Curriculum Training

    Aug 27, 2026Ireddi Rakshitha, Devavarapu Yashwanth, Ntakirutimana PierreSentence EmbeddingsAfrican Language Processing

  4. Where A Small Language Model Helps in Invoice Categorisation, Understood Through Embedding Geometry

    Aug 18, 2026Emma Ceccherini, Daniel Lawson, Anjulika SalhanSmall Language ModelsText Classification

  5. CDAE: Enhancing Perturbation Robustness in Pretrained Language Models with Contrastive Denoising

    Jul 30, 2026Sina Heydari, Amirreza Abbasi, Mohsen Hooshmand +1Contrastive LearningDenoising Autoencoders

  6. From transcription to semantic corpus analysis: unsupervised learning of sentence representations for ancient languages

    Jul 27, 2026Th{é}otime de la SelleSemantic Textual SimilaritySentence Embeddings

  7. Multilingual Sentence Embeddings for Linguistic-Integrated Reliability Audit

    Jul 20, 2026Ummugul Bezirhan, Ji Yoon Jung, Matthias von DavierSentence EmbeddingsEducational Assessment

  8. Riemannian Geometry for Pre-trained Language Model Embeddings

    Jul 8, 2026Szczepan Konior, Alexandre Quemy, Przemysław Klocek +2Sentence EmbeddingsGeometric Representation Learning

  9. Beyond Multilingual Averages: MTEB-PT, a Benchmark for Portuguese Sentence Encoders

    Jul 5, 2026Lucas Hideki Takeuchi Okamura, Alexandre Alcoforado, Anna Helena Reali CostaSentence EmbeddingsText Embedding Evaluation

  10. Evaluating Document-Tuned Transformer Representations for Person-level Mental Health Assessment

    Jun 19, 2026Aaron Marker, Oscar Kjell, Vasudha Varadarajan +1Sentence EmbeddingsMental Health

  11. Correlation Is Not Enough: Embedding Human Metadata for Individual Causal Discovery

    Jun 8, 2026Suraj Biswas, Saurabh Gupta, Pritam MukherjeeContrastive LearningSentence Embeddings

  12. Modeling semantic association in self-paced reading with language model embeddings

    Jun 5, 2026Sara Møller Østergaard, Kenneth Enevoldsen, Afra Alishahi +1Sentence EmbeddingsText Embedding Evaluation

  13. Principles of Concept Representation in Sentence Encoders

    Jun 5, 2026Isabelle Mohr, John Dujany, Jonathan Souquet +1Sentence EmbeddingsCompositional Reasoning

  14. Model-Based Quality Assessment for Massively Multilingual Parallel Data

    May 29, 2026Abdelaziz M. A. Ibrahim, Zihao Li, Jörg Tiedemann +1Sentence EmbeddingsMT Evaluation

  15. Adapting Multilingual Embedding Models to Turkish via Cross-Lingual Tokenizer Surgery and Offline Distillation

    May 28, 2026M. Ali Bayram, Banu Diri, Savaş YıldırımMultilingual Language ModelsSentence Embeddings

  16. Lost in State Space: Probing Frozen Mamba Representations

    Apr 30, 2026Bhagyashree Wagh, Akash SinghRepresentation GeometryRepresentation Collapse

  17. MIPIC: Matryoshka Representation Learning via Self-Distilled Intra-Relational and Progressive Information Chaining

    Apr 27, 2026Phung Gia Huy, Hai An Vu, Minh-Phuc Truong +4Representation LearningSentence Embeddings

  18. Finding Meaning in Embeddings: Concept Separation Curves

    Apr 23, 2026Paul Keuren, Marc Ponsen, Robert Ayoub BagheriSentence EmbeddingsText Embedding Evaluation

  19. Comparison of Modern Multilingual Text Embedding Techniques for Hate Speech Detection Task

    Apr 16, 2026Evaldas Vaiciukynas, Paulius Danenas, Linas Ablonskis +5Sentence EmbeddingsText Embedding Evaluation

  20. ViCLSR: A Supervised Contrastive Learning Framework with Natural Language Inference for Natural Language Understanding Tasks

    Mar 22, 2026Tin Van Huynh, Kiet Van Nguyen, Ngan Luu-Thuy NguyenSentence EmbeddingsSupervised Contrastive Learning