mlsanityData to 7 Oct 2026

Open Sentence Embeddings for Portuguese with the Serafim PT* encoders family

arXiv 2407.19527 ↗First posted 28 Jul 2024cs.CLcited by 4

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Abstract (arXiv)

Sentence encoder encode the semantics of their input, enabling key downstream applications such as classification, clustering, or retrieval. In this paper, we present Serafim PT*, a family of open-source sentence encoders for Portuguese with various sizes, suited to different hardware/compute budgets. Each model exhibits state-of-the-art performance and is made openly available under a permissive license, allowing its use for both commercial and research purposes. Besides the sentence encoders, this paper contributes a systematic study and lessons learned concerning the selection criteria of learning objectives and parameters that support top-performing encoders.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 18 of its 35 references that are in the map. First posted on arXiv 28 Jul 2024.

Builds on

18 of 35 references.

References · 18

  1. 2017Attention Is All You Needcited by 59,932
  2. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  3. 2018GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understandingcited by 4,854
  4. 2016MS MARCO: A Human Generated MAchine Reading COmprehension Datasetcited by 1,591
  5. 2017SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluationcited by 998
  6. 2023Towards General Text Embeddings with Multi-stage Contrastive Learningcited by 705
  7. 2022MTEB: Massive Text Embedding Benchmarkcited by 623
  8. 2020Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillationcited by 591
  9. 2017Efficient Natural Language Response Suggestion for Smart Replycited by 228
  10. 2021TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learningcited by 116
  11. 2021mMARCO: A Multilingual Version of the MS MARCO Passage Ranking Datasetcited by 116
  12. 2023AnglE-optimized Text Embeddingscited by 98
6 more
  1. 2024GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuningcited by 40
  2. 2022Toward Efficient Language Model Pretraining and Downstream Adaptation via Self-Evolution: A Case Study on SuperGLUEcited by 24
  3. 2023Advancing Neural Encoding of Portuguese with Transformer Albertina PT-*cited by 24
  4. 2024Advancing Generative AI for Portuguese with Open Decoder Gerv'asio PT*cited by 19
  5. 2024Fostering the Ecosystem of Open Neural Encoders for Portuguese with Albertina PT* Familycited by 8
  6. 2024PORTULAN ExtraGLUE Datasets and Models: Kick-starting a Benchmark for the Neural Processing of Portuguesecited by 5

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 4.

4 papers.

  1. 2026Sovereign AI-based Public Services are Viable and Affordablecited by 1
  2. 2026Beyond Multilingual Averages: MTEB-PT, a Benchmark for Portuguese Sentence Encoderscited by 1
  3. 2026MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguesecited by 0
  4. 2026Language Models for Portuguese: A Systematic Mapping Studycited by 0