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cs.CL2024

Exploring Large Language Models for Product Attribute Value Identification

Kassem Sabeh, Mouna Kacimi, Johann Gamper +2

Product attribute value identification (PAVI) involves automatically identifying attributes and their values from product information, enabling features like product search, recomm…

cs.CL2024

MaiNLP at SemEval-2024 Task 1: Analyzing Source Language Selection in Cross-Lingual Textual Relatedness

Shijia Zhou, Huangyan Shan, Barbara Plank +1

This paper presents our system developed for the SemEval-2024 Task 1: Semantic Textual Relatedness (STR), on Track C: Cross-lingual. The task aims to detect semantic relatedness of…

cs.CL20231 cited

Vicinal Risk Minimization for Few-Shot Cross-lingual Transfer in Abusive Language Detection

Gretel Liz De la Peña Sarracén, Paolo Rosso, Robert Litschko +2

Cross-lingual transfer learning from high-resource to medium and low-resource languages has shown encouraging results. However, the scarcity of resources in target languages remain…

cs.CL2023

Establishing Trustworthiness: Rethinking Tasks and Model Evaluation

Robert Litschko, Max Müller-Eberstein, Rob van der Goot +2

Language understanding is a multi-faceted cognitive capability, which the Natural Language Processing (NLP) community has striven to model computationally for decades. Traditionall…

cs.CL2023

Boosting Zero-shot Cross-lingual Retrieval by Training on Artificially Code-Switched Data

Robert Litschko, Ekaterina Artemova, Barbara Plank

Transferring information retrieval (IR) models from a high-resource language (typically English) to other languages in a zero-shot fashion has become a widely adopted approach. In…

cs.CL2023

A General-Purpose Multilingual Document Encoder

Onur Galoğlu, Robert Litschko, Goran Glavaš

Massively multilingual pretrained transformers (MMTs) have tremendously pushed the state of the art on multilingual NLP and cross-lingual transfer of NLP models in particular. Whil…