Adapting TBXTools to automatic terminology extraction with BERT

Modelling specialized language through AI: challenges in training systems for technical domain translation

Modelling specialized language with artificial intelligence is a significant challenge for specialized translation, especially in fields where controlled terminology is essential, such as medicine, engineering, law, or the exact sciences. The performance of neural machine translation systems depends directly on the qua...

SalamandraTA at WMT 2026 Terminology Shared Task: Hard Examples Are Better Teachers

Terminology-aware translation asks for more than a correct translation: the output must use the exact terms a glossary prescribes. The standard recipe, fine-tuning on glossary-annotated translation pairs, hides an inefficiency: for most examples the glossary prescribes exactly what the model would have produced anyway,...

TransClean: A Benchmark for Detecting and Extracting Clean Translations from Large Language Model Outputs

This work analyzes over 790,000 translation outputs from 12 LLMs across 22 language pairs (LPs) and identifies 12 recurring noise patterns, which are group into formatting and content noise, and constructs TransClean, a controlled benchmark of 9,900 pairs of noisy and clean translation outputs.

Using Large Language Models for Automated Corpus Annotation and Linguistic Analysis: A Critical Methodological Framework

This article argues against unvalidated full automation and proposes selective automation, disagreement-based human adjudication, model/version documentation, and preservation of raw outputs for corpus research and develops a validated human–LLM workflow for corpus research.

A unified framework and benchmark for generalizable biomedical knowledge extraction and applications with large language models

Results demonstrate that InfoFlowEX equips LLMs with robust adaptability, achieving consistent gains over baselines with minimal task-specific customization, highlighting InfoFlowEX for real-world biomedical applications.

Context-Aware Detection of Specialized Language