6 papers
Cross-Modal Robustness Transfer (CMRT): Training Robust Speech Translation Models Using Adversarial Text
Abderrahmane Issam, Yusuf Can Semerci, Jan Scholtes +1
End-to-End Speech Translation (E2E-ST) has seen significant advancements, yet current models are primarily benchmarked on curated, "clean" datasets. This overlooks critical real-wo…
From FusHa to Folk: Exploring Cross-Lingual Transfer in Arabic Language Models
Abdulmuizz Khalak, Abderrahmane Issam, Gerasimos Spanakis
Arabic Language Models (LMs) are pretrained predominately on Modern Standard Arabic (MSA) and are expected to transfer to its dialects. While MSA as the standard written variety is…
Maastricht University at AMIYA: Adapting LLMs for Dialectal Arabic using Fine-tuning and MBR Decoding
Abdulhai Alali, Abderrahmane Issam
Large Language Models (LLMs) are becoming increasingly multilingual, supporting hundreds of languages, especially high resource ones. Unfortunately, Dialect variations are still un…
A Study of Crosslinguistic Influence in Language Models
Abderrahmane Issam, Yusuf Can Semerci, Jan Scholtes +1
The sequential acquisition of languages inevitably leads to Crosslinguistic Influence (CLI), where the syntactic properties of a first language (L1) impact the processing of a seco…
DTW-Align: Bridging the Modality Gap in End-to-End Speech Translation with Dynamic Time Warping Alignment
Abderrahmane Issam, Yusuf Can Semerci, Jan Scholtes +1
End-to-End Speech Translation (E2E-ST) is the task of translating source speech directly into target text bypassing the intermediate transcription step. The representation discrepa…
A Representation Level Analysis of NMT Model Robustness to Grammatical Errors
Abderrahmane Issam, Yusuf Can Semerci, Jan Scholtes +1
Understanding robustness is essential for building reliable NLP systems. Unfortunately, in the context of machine translation, previous work mainly focused on documenting robustnes…