Hugging Face Trending Papers

DenseOn with the LateOn: Fully Open Dense and Late-Interaction Models for Multilingual, Long-Context, and Code Search

State-of-the-art retrieval models increasingly rely on closed training data, creating a reproducibility gap. We present an open end-to-end recipe for training retrieval models and study how English supervision transfers to multilingual retrieval through translate-train.

arXiv AI

Jun 12

SkMTEB: Slovak Massive Text Embedding Benchmark and Model Adaptation

arXiv:2606. 13647v1 Announce Type: cross Abstract: We introduce SkMTEB, the first comprehensive MTEB-style text embedding benchmark for Slovak, a low-resource West Slavic language, comprising 31 datasets across 7 task types -- nearly 4$\times$ the depth of existing multilingual benchmark coverage for Slovak.

By Marek \v{S}uppa, Andrej Ridzik, Daniel Hl\'adek, Nat\'alia K\v{n}a\v{z}ekov\'a, Vikt\'oria Ondrejov\'a

rag fine-tuning benchmarks

arXiv AI

Jul 7

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

arXiv:2607. 04071v1 Announce Type: cross Abstract: Portuguese remains underrepresented in text embedding evaluation, despite being one of the most widely spoken languages in the world.

By Lucas Hideki Takeuchi Okamura, Alexandre Alcoforado, Anna Helena Reali Costa

rag fine-tuning benchmarks

arXiv AI

Jul 1

Cross-lingual Relation Extraction with Large Language Models: Zero-Shot, Few-Shot, and Fine-Tuned Evaluation on Romanian

arXiv:2606. 31718v1 Announce Type: cross Abstract: Relation extraction (RE) for low-resource languages is typically constrained by the lack of annotated corpora.

By Dragos-Mitrut Vasile, Elena-Simona Apostol, Stefan-Adrian Toma, Adrian Paschke, Ciprian-Octavian Truica

llms fine-tuning benchmarks

arXiv Machine Learning

Aug 11

Embedding Initialization for Unseen Low-resource Languages in Multilingual NMT: A Case Study on Limbum-English Translation

arXiv:2608. 07629v1 Announce Type: cross Abstract: Multilingual neural machine translation models such as NLLB-200 cover 200 languages but leave thousands unsupported, including most Grassfields Bantu languages of Cameroon.

By Samiratu Ntohsi, Neza David Tuyishimire, Anesu Kafesu, Marvin Ogore, Samuel Oluwajunwonlo Babalola, Oche Ankeli

llms rag nlp fine-tuning

arXiv AI

Jul 29

Building Large-Scale English-Romanian Literary Translation Resources with Open Models

arXiv:2509. 07829v4 Announce Type: replace-cross Abstract: Literary translation has recently gained attention as a distinct and complex task in machine translation research, yet translation by small open models remains an open problem, particularly for low-resource languages such as Romanian.

By Mihai Nadas, Laura Diosan, Andreea Tomescu, Andrei Piscoran

llms nlp fine-tuning

arXiv Machine Learning

Aug 4

LangFIR: Discovering Sparse Language-Specific Features from Monolingual Data for Language Steering

arXiv:2604. 03532v2 Announce Type: replace-cross Abstract: Large language models (LLMs) show strong multilingual capabilities, yet reliably controlling the language of their outputs remains difficult.

By Sing Hieng Wong, Hassan Sajjad, A. B. Siddique

llms benchmarks

arXiv AI

Jun 2

EuroBERT: Scaling Multilingual Encoders for European Languages

arXiv:2503. 05500v3 Announce Type: replace-cross Abstract: General-purpose multilingual vector representations, used in retrieval, regression and classification, are traditionally obtained from bidirectional encoder models.

By Nicolas Boizard, Hippolyte Gisserot-Boukhlef, Duarte M. Alves, Andr\'e Martins, Ayoub Hammal, Caio Corro, C\'eline Hudelot, Emmanuel Malherbe, Etienne Malaboeuf, Fanny Jourdan, Gabriel Hautreux, Jo\~ao Alves, Kevin El Haddad, Manuel Faysse, Maxime Peyrard, Nuno M. Guerreiro, Patrick Fernandes, Ricardo Rei, Pierre Colombo

Hugging Face Trending Papers

Jul 1

MultiSynt/MT: Trillion-Token Multi-Parallel Pre-Training Data Translated Across 36 Languages

Open web-scale pre-training corpora remain concentrated in English, limiting multilingual LLM development. We introduce MultiSynt/MT, an open synthetic parallel corpus with approximately 4.

llms benchmarks

arXiv AI

Aug 6

Teaching Nemotron Greek: Mining a Corpus, Adapting Retrieval, and Grounding Generation for Modern Greek across Specialist Domains

arXiv:2608. 05138v1 Announce Type: cross Abstract: Modern Greek is absent from NVIDIA's Nemotron retrieval models and from major multilingual retrieval benchmarks, despite being important for retrieval-augmented generation (RAG) in legal, energy, financial, and medical applications.

By Ayoub Kirouane, Christos Petrocheilos

rag fine-tuning benchmarks

arXiv AI

Jun 9

Multilingual Training and Evaluation Resources for Vision-Language Models

arXiv:2604. 18347v2 Announce Type: replace-cross Abstract: Vision Language Models (VLMs) achieved rapid progress in the recent years.

By Daniela Baiamonte, Elena Fano, Matteo Gabburo, Stefano Simonazzi, Leonardo Rigutini, Andrea Zugarini

llms multimodal benchmarks

arXiv AI

Aug 7

Breaking the Curse of Multilinguality in Many-to-Many Speech-to-Text Translation via a Resource-Aware Mixture of Speech Encoders

arXiv:2608. 04586v2 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) have achieved significant success in speech-to-text translation (S2TT).

By Yexing Du, Kaiyuan Liu, Youcheng Pan, Bo Yang, Chengpeng Fu, Yu Wang, Ming Liu

llms multimodal benchmarks safety

arXiv Machine Learning

Jul 7

TokSuite: Measuring the Impact of Tokenizer Choice on Language Model Behavior

arXiv:2512. 20757v2 Announce Type: replace-cross Abstract: Tokenizers provide the fundamental basis through which text is represented and processed by language models (LMs).

By G\"ul Sena Alt{\i}nta\c{s}, Malikeh Ehghaghi, Brian Lester, Fengyuan Liu, Wanru Zhao, Marco Ciccone, Colin Raffel

llms nlp benchmarks

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