36 citations · 154 across the 56 of their papers we have counts for
8 papers · 2 filters
MATCHED: Multimodal Authorship-Attribution To Combat Human Trafficking in Escort-Advertisement Data
Vageesh Saxena, Benjamin Bashpole, Gijs Van Dijck +1
Human trafficking (HT) remains a critical issue, with traffickers increasingly leveraging online escort advertisements (ads) to advertise victims anonymously. Existing detection me…
Analyzing the Attention Heads for Pronoun Disambiguation in Context-aware Machine Translation Models
Paweł Mąka, Yusuf Can Semerci, Jan Scholtes +1
In this paper, we investigate the role of attention heads in Context-aware Machine Translation models for pronoun disambiguation in the English-to-German and English-to-French lang…
LegalLens Shared Task 2024: Legal Violation Identification in Unstructured Text
Ben Hagag, Liav Harpaz, Gil Semo +5
This paper presents the results of the LegalLens Shared Task, focusing on detecting legal violations within text in the wild across two sub-tasks: LegalLens-NER for identifying leg…
Know When to Fuse: Investigating Non-English Hybrid Retrieval in the Legal Domain
Antoine Louis, Gijs van Dijck, Gerasimos Spanakis
Hybrid search has emerged as an effective strategy to offset the limitations of different matching paradigms, especially in out-of-domain contexts where notable improvements in ret…
Fixed and Adaptive Simultaneous Machine Translation Strategies Using Adapters
Abderrahmane Issam, Yusuf Can Semerci, Jan Scholtes +1
Simultaneous machine translation aims at solving the task of real-time translation by starting to translate before consuming the full input, which poses challenges in terms of bala…
ColBERT-XM: A Modular Multi-Vector Representation Model for Zero-Shot Multilingual Information Retrieval
Antoine Louis, Vageesh Saxena, Gijs van Dijck +1
State-of-the-art neural retrievers predominantly focus on high-resource languages like English, which impedes their adoption in retrieval scenarios involving other languages. Curre…
Sequence Shortening for Context-Aware Machine Translation
Paweł Mąka, Yusuf Can Semerci, Jan Scholtes +1
Context-aware Machine Translation aims to improve translations of sentences by incorporating surrounding sentences as context. Towards this task, two main architectures have been a…
Triple-Encoders: Representations That Fire Together, Wire Together
Justus-Jonas Erker, Florian Mai, Nils Reimers +2
Search-based dialog models typically re-encode the dialog history at every turn, incurring high cost. Curved Contrastive Learning, a representation learning method that encodes rel…