Tianyu Gao
8 papers in the PaperMetrix corpus
Papers by this author
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Low-Rank and Sparse Matrix Factorization for Scientific Paper Recommendation in Heterogeneous Network
2018 · IEEE Access
With the rapid growth of scientific publications, it is hard for researchers to acquire appropriate papers that meet their expectations. Recommendation system for scientific articles is an essential technology to overcome this problem. In this …
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Learning from Context or Names? An Empirical Study on Neural Relation Extraction
2020
Neural models have achieved remarkable success on relation extraction (RE) benchmarks. However, there is no clear understanding which type of information affects existing RE models to make decisions and how to further improve the performance …
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OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction
2019
Xu Han, Tianyu Gao, Yuan Yao, Deming Ye, Zhiyuan Liu, Maosong Sun. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): …
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FewRel 2.0: Towards More Challenging Few-Shot Relation Classification
2019
Tianyu Gao, Xu Han, Hao Zhu, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language …
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KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation
2019 · arXiv (Cornell University)
Pre-trained language representation models (PLMs) cannot well capture factual knowledge from text. In contrast, knowledge embedding (KE) methods can effectively represent the relational facts in knowledge graphs (KGs) with informative entity embeddings, but conventional KE …
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KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation
2021 · Transactions of the Association for Computational Linguistics
Abstract Pre-trained language representation models (PLMs) cannot well capture factual knowledge from text. In contrast, knowledge embedding (KE) methods can effectively represent the relational facts in knowledge graphs (KGs) with informative entity embeddings, but conventional …
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SimCSE: Simple Contrastive Learning of Sentence Embeddings
2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
This paper presents SimCSE, a simple contrastive learning framework that greatly advances the state-of-the-art sentence embeddings. We first describe an unsupervised approach, which takes an input sentence and predicts itself in a contrastive objective, with …
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Making Pre-trained Language Models Better Few-shot Learners
2021
Tianyu Gao, Adam Fisch, Danqi Chen. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 2021.