9 papers · 1 filter
Domain-specific or Uncertainty-aware models: Does it really make a difference for biomedical text classification?
Aman Sinha, Timothee Mickus, Marianne Clausel +2
The success of pretrained language models (PLMs) across a spate of use-cases has led to significant investment from the NLP community towards building domain-specific foundational…
AXOLOTL'24 Shared Task on Multilingual Explainable Semantic Change Modeling
Mariia Fedorova, Timothee Mickus, Niko Partanen +3
This paper describes the organization and findings of AXOLOTL'24, the first multilingual explainable semantic change modeling shared task. We present new sense-annotated diachronic…
A Comparison of Language Modeling and Translation as Multilingual Pretraining Objectives
Zihao Li, Shaoxiong Ji, Timothee Mickus +2
Pretrained language models (PLMs) display impressive performances and have captured the attention of the NLP community. Establishing best practices in pretraining has, therefore, b…
I Have an Attention Bridge to Sell You: Generalization Capabilities of Modular Translation Architectures
Timothee Mickus, Raúl Vázquez, Joseph Attieh
Modularity is a paradigm of machine translation with the potential of bringing forth models that are large at training time and small during inference. Within this field of study,…
SemEval-2024 Shared Task 6: SHROOM, a Shared-task on Hallucinations and Related Observable Overgeneration Mistakes
Timothee Mickus, Elaine Zosa, Raúl Vázquez +5
This paper presents the results of the SHROOM, a shared task focused on detecting hallucinations: outputs from natural language generation (NLG) systems that are fluent, yet inaccu…
Can Machine Translation Bridge Multilingual Pretraining and Cross-lingual Transfer Learning?
Shaoxiong Ji, Timothee Mickus, Vincent Segonne +1
Multilingual pretraining and fine-tuning have remarkably succeeded in various natural language processing tasks. Transferring representations from one language to another is especi…