1 code implementation • EMNLP 2021 • Ashkan Alinejad, Hassan S. Shavarani, Anoop Sarkar
In simultaneous machine translation, finding an agent with the optimal action sequence of reads and writes that maintain a high level of translation quality while minimizing the average lag in producing target tokens remains an extremely challenging problem.
1 code implementation • 23 Oct 2023 • Hassan S. Shavarani, Anoop Sarkar
Entity linking is a prominent thread of research focused on structured data creation by linking spans of text to an ontology or knowledge source.
Ranked #1 on Entity Linking on AIDA/testc (using extra training data)
1 code implementation • EACL 2021 • Hassan S. Shavarani, Anoop Sarkar
Adding linguistic information (syntax or semantics) to neural machine translation (NMT) has mostly focused on using point estimates from pre-trained models.
1 code implementation • 17 Sep 2019 • Jetic Gū, Hassan S. Shavarani, Anoop Sarkar
Neural machine translation (NMT) systems require large amounts of high quality in-domain parallel corpora for training.
no code implementations • LREC 2020 • Hassan S. Shavarani, Satoshi Sekine
Wikipedia is a great source of general world knowledge which can guide NLP models better understand their motivation to make predictions.
no code implementations • EMNLP 2018 • Jetic Gū, Hassan S. Shavarani, Anoop Sarkar
The addition of syntax-aware decoding in Neural Machine Translation (NMT) systems requires an effective tree-structured neural network, a syntax-aware attention model and a language generation model that is sensitive to sentence structure.