This paper presents a study on improving healthcare-domain translation for four low-resource languages using Arabic and Persian as pivots, and introduces three transfer strategies.

This paper introduces a new R package for Non-negative Matrix Factorization (NMF) and compares its performance systematically with two other R packages using real-world data.

This paper introduces SkMTEB, a comprehensive text embedding benchmark for Slovak, and develops efficient, locally-deployable Slovak embeddings.

This paper introduces a pipeline to extract grammatical rules, example sentences, and lexicons from grammar books and generates synthetic parallel corpora for fine-tuning machine translation models on…

The paper proposes decomposing the assessment of massive multilingual parallel data into separate parallelism and quality estimation components, concluding that no single universal metric is reliable…

This paper introduces KliniskVestBERT, a suite of BERT models specialized by pre-training on a large, diverse corpus of real-world Norwegian clinical texts, demonstrating superior performance for clin…

This paper explores the integration of several extensions for Natural Language to SQL (NL2SQL) translation, including NatSQL representation, preprocessing, fine-tuning, and reranker model.

The authors present ZONOS2 8B, a TTS model with improved naturalness, prosody, and voice cloning fidelity, achieved through scaling, data expansion, and simplification.

This paper introduces BamiBERT, a new Vietnamese language model based on BERT that addresses limitations of PhoBERT and sets a new state-of-the-art among base-sized Vietnamese encoders.

This paper introduces PETRA, a large-scale Petroleum Engineering Text for Retrieval Adaptation dataset and pipeline that converts noisy public web data into a curated domain corpus and synthetic super…

The paper introduces an LLM-based pipeline that tags learning resources with structured competencies, achieving strong performance while providing traceable evidence and leveraging graph constraints.

The paper introduces PetroBench, a comprehensive benchmark for evaluating Large Language Models across various domains of petroleum engineering, finding that models perform better on subjective tasks…

This paper proposes a source-free continual test-time adaptation methodology using a controlled teacher adaptation and class prototype estimation.

This paper proposes a neural architecture for Quranic Passage Retrieval using hybrid candidate retrieval, semantic reranking, confidence gating, and multi-verse aggregation.

The paper proposes MACAT, a Multi-Agent Culture-Aware Translation framework, to selectively translate culture-loaded words in ancient Chinese texts, achieving superior performance over existing method…

This paper presents the benefits of visual pretraining for foundation model intelligence, outperforming text-only pretraining on multiple backbones and benchmarks.

This paper introduces MMed-Bench-IR, a benchmark for multilingual medical retrieval in clinical settings, evaluating cross-lingual alignment, concept discrimination, and evidence retrieval.

The paper introduces a new benchmark for multi-target cross-lingual summarization (MTXLS) and proposes an activation steering method that significantly improves LLM performance by guiding the generati…

The paper introduces GigaSpeechBench, a comprehensive multilingual and multidimensional ASR & AST benchmark with 680 hours of human-annotated speech, featuring 12 low-resource languages, 6 Chinese dia…