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SQuARE: Towards Multi-Domain and Few-Shot Collaborating Question Answering Agents

ODSC - Open Data Science

Examples are the ACL fellow award 2020 and the first Hessian LOEWE Distinguished Chair award (2,5 mil. Iryna is co-director of the NLP program within ELLIS, a European network of excellence in machine learning. She is currently the president of the Association of Computational Linguistics. Euro) in 2021.

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A Gentle Introduction to GPTs

Mlearning.ai

GPT-3 is a autoregressive language model created by OpenAI, released in 2020 . OpenAI’s research paper on the GPT-3, “Language Models are Few-Shot Learners” was released in May 2020 and it outlined the fact that state-of-the-art GPT-3 generated text is nearly indistinguishable to that of the text written by humans. What is GPT-3?

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The State of Multilingual AI

Sebastian Ruder

This post is partially based on a keynote I gave at the Deep Learning Indaba 2022. These include groups focusing on linguistic regions such as Masakhane for African languages, AmericasNLP for native American languages, IndoNLP for Indonesian languages, GhanaNLP and HausaNLP , among others.

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All Languages Are NOT Created (Tokenized) Equal

Topbots

70% of research papers published in a computational linguistics conference only evaluated English.[ In Findings of the Association for Computational Linguistics: ACL 2022 , pages 2340–2354, Dublin, Ireland. Association for Computational Linguistics. Association for Computational Linguistics.

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Overcoming The Limitations Of Large Language Models

Topbots

In the past, the Deep Learning community solved the data shortage with self-supervision — pre-training LLMs using next-token prediction, a learning signal that is available “for free” since it is inherent to any text. Association for Computational Linguistics. [2] Association for Computational Linguistics. [4]

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ML and NLP Research Highlights of 2021

Sebastian Ruder

  Retrieval-augmented language models, which integrate retrieval into pre-training and downstream usage, have already featured in my highlights of 2020. A framework for self-supervised learning of speech representations. Advances in Neural Information Processing Systems, 2020. In Proceedings of ICLR 2020. Subbiah, M.,

NLP 52
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Testing the Robustness of LSTM-Based Sentiment Analysis Models

John Snow Labs

The creation of the LSTM-based sentiment analysis model will provide a thorough method for using deep learning techniques for analyzing human sentiment from textual data, leveraging PyTorch’s flexibility and efficiency. Learning Word Vectors for Sentiment Analysis. Gopalakrishnan, K., & Salem, F. abs/2005.03993 Andrew L.