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Deep Multi-Tasking Models

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Lizzie S. and 4 others
Deep Multi-Tasking Models

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The MLAI Meetup is a community for AI researchers and professionals which hosts monthly talks on exciting research. Our format is:

  • 6:00 - 6:20: Socializing
  • 6:20 - 6:40: Announcements and AI news
  • 6:40 - 7:40: Talk(s) and Q&A
  • 7:40 - 8:00 Networking
  • 8:00: Head to the nearest pub for dinner

Speaker: Angel Felipe Magnossao de Paula

Talk: Mitigating Negative Transfer with Task Awareness for Sexism, Hate Speech, and Toxic Language Detection

Abstract: This paper proposes a novelty approach to mitigate the negative transfer problem. In the field of machine learning, the common strategy is to apply the Single-Task Learning approach in order to train a supervised model to solve a specific task. Training a robust model requires a lot of data and a significant amount of computational resources, making this solution unfeasible in cases where data are unavailable or expensive to gather. Therefore another solution, based on the sharing of information between tasks, has been developed: Multi-task Learning (MTL). Despite the recent developments regarding MTL, the problem of negative transfer has still to be solved. Negative transfer is a phenomenon that occurs when noisy information is shared between tasks, resulting in a drop in performance. This paper proposes a new approach to mitigate the negative transfer problem based on the task awareness concept. The proposed approach results in diminishing the negative transfer together with an improvement of performance over classic MTL solution. Moreover, the proposed approach has been implemented in two unified architectures to detect Sexism, Hate Speech, and Toxic Language in text comments. The proposed architectures set a new state-of-the-art both in EXIST-2021 and HatEval-2019 benchmarks.

Speaker Bio: Angel Magnossão de Paula (Angel) is a third-year PhD candidate in the Computer Science program at the Universitat Politècnica de València in Valencia, Spain. He earned his B.Sc. in engineering from FEI University Center in 2015 and his M.Sc. in computer engineering from the Universidade de São Paulo in 2021, both in São Paulo, Brazil. Angel is also an assistant researcher at the University of Melbourne and RMIT University. His research interests include machine learning, deep learning, and natural language processing.

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