News

16/05/2024: Vijini successfully defended her PhD on Detection of LLM-generated academic content. Congrats!

02/05/2024: ICML paper accepted!

16/03/2021: Welcome to Vijini Liyanage to RCLN, our new PhD student

19/11/2019: Our poster at the 5th Franco-Polish forum for Research and Innovation has been awarded! https://twitter.com/davidebus/status/1196795155791122432

29/10/2019: Our paper "Frame-Based Detection of Figurative Language in Tweets" is now available on IEEEXplore: https://ieeexplore.ieee.org/document/8870226

11/07/2019: Our paper "Frame-Based Detection of Figurative Language in Tweets" has been accepted for publication in the IEEE Computational Intelligence Magazine!

13/06/2019: I'm glad to have been nominated as a member of the board of the steering commitee for HLT by the French Association for Artificial Intelligence.

10/12/2018: I'll be part of the organizing committee of the 2nd workshop on Deep Learning for Knowledge Graphs, co-located at ESWC 2019. The site is online here https://alammehwish.github.io/dl4kg-eswc/ 

22/11/2018: The EU Project PhilHumans is accepted! LIPN is a partner of the project and I will be the local supervisor

The proceedings of the 5th SemWebEval challenge at ESWC 2018 are available at Springer!

They are part of the CCIS series

https://www.springer.com/us/book/9783030000714

"This book constitutes the thoroughly refereed post conference proceedings of the 4th edition of the Semantic Web Evaluation Challenge, SemWebEval 2018, co-located with the 15th European Semantic Web conference, held in Heraklion, Greece, in June 2018.

This book includes the descriptions of all methods and tools that competed at SemWebEval 2018, together with a detailed description of the tasks, evaluation procedures and datasets. The 18 revised full papers presented in this volume were carefully reviewed and selected from 24 submissions. The contributions are grouped in the areas: the mighty storage challenge; open knowledge extraction challenge; question answering over linked data challenge; semantic sentiment analysis."