Language and Multimodal AI Lab (LAMA)

The Language and Multimodal AI Lab (LAMA) aims to develop machine learning algorithms for language understanding and generation following a holistic approach where language can be combined with other types of information. In addition to textual context of varying length, our models include knowledge in the form of images, videos, audio recordings, sensor data, metadata and knowledge bases. Multimodal machine learning is therefore at the core of our research. The main areas we work on include (multimodal) language generation, machine translation, text adaptation, image captioning, transfer learning for language, NLP for health and sustainable development, quality evaluation and estimation, and language learning applications.

Recent Publications

News and Highlights

  • 22/04/2022: 1 paper accepted to IJCAI-ECAI 2022.
  • 08/04/2022: 2 papers accepted to NAACL 2022.
  • 06/04/2022: 4 papers accepted to LREC 2022.
  • 23/02/2022: 2 papers accepted to ACL 2022.
  • 30/11/2021: 1 paper accepted to AAAI 2022.
  • 15/10/2021: 1 paper accepted to BMVC 2021.
  • 25/08/2021: 3 papers accepted to EMNLP(Findings) and EMNLP (Demo) 2021.
  • 05/05/2021: 4 papers accepted to ACL and ACL(Findings) 2021.
  • 10/03/2021: 2 papers accepted to NAACL 2021.
  • 14/01/2021: 4 papers accepted to EACL 2021.
  • 08/12/2020: Curious Case of Language Generation Evaluation Metrics: A Cautionary Tale to appear at COLING 2020.
  • 04/12/2020: An Exploratory Study on Multilingual Quality Estimation to appear at AACL 2020.
  • 21/11/2020: Our lab is online!