38 citations · 238 across the 42 of their papers we have counts for
9 papers · 1 filter
Multi3WOZ: A Multilingual, Multi-Domain, Multi-Parallel Dataset for Training and Evaluating Culturally Adapted Task-Oriented Dialog Systems
Songbo Hu, Han Zhou, Mete Hergul +5
Creating high-quality annotated data for task-oriented dialog (ToD) is known to be notoriously difficult, and the challenges are amplified when the goal is to create equitable, cul…
Cross-Lingual Transfer with Target Language-Ready Task Adapters
Marinela Parović, Alan Ansell, Ivan Vulić +1
Adapters have emerged as a modular and parameter-efficient approach to (zero-shot) cross-lingual transfer. The established MAD-X framework employs separate language and task adapte…
Distilling Efficient Language-Specific Models for Cross-Lingual Transfer
Alan Ansell, Edoardo Maria Ponti, Anna Korhonen +1
Massively multilingual Transformers (MMTs), such as mBERT and XLM-R, are widely used for cross-lingual transfer learning. While these are pretrained to represent hundreds of langua…
Translation-Enhanced Multilingual Text-to-Image Generation
Yaoyiran Li, Ching-Yun Chang, Stephen Rawls +2
Research on text-to-image generation (TTI) still predominantly focuses on the English language due to the lack of annotated image-caption data in other languages; in the long run,…
Detecting and Mitigating Hallucinations in Multilingual Summarisation
Yifu Qiu, Yftah Ziser, Anna Korhonen +2
Hallucinations pose a significant challenge to the reliability of neural models for abstractive summarisation. While automatically generated summaries may be fluent, they often lac…
Transfer-Free Data-Efficient Multilingual Slot Labeling
Evgeniia Razumovskaia, Ivan Vulić, Anna Korhonen
Slot labeling (SL) is a core component of task-oriented dialogue (ToD) systems, where slots and corresponding values are usually language-, task- and domain-specific. Therefore, ex…
Language-Agnostic Bias Detection in Language Models with Bias Probing
Abdullatif Köksal, Omer Faruk Yalcin, Ahmet Akbiyik +3
Pretrained language models (PLMs) are key components in NLP, but they contain strong social biases. Quantifying these biases is challenging because current methods focusing on fill…
LongForm: Effective Instruction Tuning with Reverse Instructions
Abdullatif Köksal, Timo Schick, Anna Korhonen +1
Instruction tuning enables language models to more effectively generalize and better follow user intent. However, obtaining instruction data is costly and challenging. Prior work e…
AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning
Han Zhou, Xingchen Wan, Ivan Vulić +1
Large pretrained language models are widely used in downstream NLP tasks via task-specific fine-tuning, but such procedures can be costly. Recently, Parameter-Efficient Fine-Tuning…