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Contextualized entity representations learned by state-of-the-art transformer-based language models (TLMs) like BERT, GPT, T5, etc., leverage the attention mechanism to learn the data context from training data corpus.
Superglue: A stickier benchmark for general-purpose language understanding systems
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Sensebert: Driving some sense into BERT
Yoav Levine, Barak Lenz, Or Dagan, Ori Ram, Dan Padnos, Or Sharir, Shai Shalev-Shwartz, Amnon Shashua, and Yoav Shoham · 2020
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Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio. 2018 · 2018
Cited alongside, same era.
Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R Bowman. 2018 · 2018
Cited alongside, same era.
Glossbert: BERT for word sense disambiguation with gloss knowledge
Luyao Huang, Chi Sun, Xipeng Qiu, and Xuanjing Huang. 2019 · 2019
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Zero-shot word sense disambiguation using sense definition embeddings
Sawan Kumar, Sharmistha Jat, Karan Saxena, and Partha P. Talukdar. 2019 · 2019
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Adaptive learning machine for score improvement and parts thereof
Keyur Faldu, Aditi Avasthi, and Achint Thomas. 2020a
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System and method for behavioral analysis and recommendations
Keyur Faldu, Achint Thomas, and Aditi Avasthi. 2020b
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System and method for recommending personalized content using contextualized knowledge base
Keyur Faldu, Achint Thomas, and Aditi Avasthi. 2020c
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Leap-of-thought: Teaching pre-trained models to systematically reason over implicit knowledge
Alon Talmor, Oyvind Tafjord, Peter Clark, Yoav Goldberg, and Jonathan Berant. 2020 · 2020
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System and method for personalized retrieval of academic content in a hierarchical manner
Achint Thomas, Keyur Faldu, and Aditi Avasthi. 2020 · 2020
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Semantics of the black-box: Can knowledge graphs help make deep learning systems more interpretable and explainable?
Manas Gaur, Keyur Faldu, and Amit P. Sheth. 2021 · 2021
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