no code implementations • LREC 2022 • Yuqian Dai, Marc de Kamps, Serge Sharoff
Pre-trained transformer-based models, such as BERT, have shown excellent performance in most natural language processing benchmark tests, but we still lack a good understanding of the linguistic knowledge of BERT in Neural Machine Translation (NMT).
no code implementations • 22 May 2023 • Yuqian Dai, Serge Sharoff, Marc de Kamps
Although the Transformer model can effectively acquire context features via a self-attention mechanism, deeper syntactic knowledge is still not effectively modeled.
no code implementations • 22 May 2023 • Yuqian Dai, Serge Sharoff, Marc de Kamps
Moreover, GAT is more competitive in training speed and syntactic dependency prediction than MT-B, which may reveal a better incorporation of modeling explicit syntactic knowledge and the possibility of combining GAT and BERT in the MT tasks.
no code implementations • 14 Jan 2022 • Benedikt Feldotto, Cristian Soare, Alois Knoll, Piyanee Sriya, Sarah Astill, Marc de Kamps, Samit Chakrabarty
We use our framework to analyze raw EMG data collected during an isometric knee extension study to identify synergies that drive a musculoskeletal lower limb model.