Revisiting and Advancing Chinese Natural Language Understanding with Accelerated Heterogeneous Knowledge Pre-training
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Xiaofeng He | J. Wang | Ang Wang | Taolin Zhang | Chengyu Wang | Junwei Dong | Yinghui Liu | J. Huang | Y. Li
[1] Minghui Qiu,et al. EasyNLP: A Comprehensive and Easy-to-use Toolkit for Natural Language Processing , 2022, EMNLP.
[2] Andrew M. Dai,et al. PaLM: Scaling Language Modeling with Pathways , 2022, J. Mach. Learn. Res..
[3] Ting Liu,et al. PERT: Pre-training BERT with Permuted Language Model , 2022, ArXiv.
[4] Juan Manuel Pérez,et al. RoBERTuito: a pre-trained language model for social media text in Spanish , 2021, LREC.
[5] Shijin Wang,et al. Continual Pre-training of Language Models for Math Problem Understanding with Syntax-Aware Memory Network , 2022, ACL.
[6] Jian Yang,et al. A Survey of Knowledge Enhanced Pre-trained Models , 2021, ArXiv.
[7] Zhuowen Tu,et al. Convolutions and Self-Attention: Re-interpreting Relative Positions in Pre-trained Language Models , 2021, ACL.
[8] Frank Rudzicz,et al. How is BERT surprised? Layerwise detection of linguistic anomalies , 2021, ACL.
[9] Songfang Huang,et al. Lattice-BERT: Leveraging Multi-Granularity Representations in Chinese Pre-trained Language Models , 2021, NAACL.
[10] Alex Suhan,et al. LazyTensor: combining eager execution with domain-specific compilers , 2021, ArXiv.
[11] Catherine Havasi,et al. Combining pre-trained language models and structured knowledge , 2021, ArXiv.
[12] Hyunjae Lee,et al. KoreALBERT: Pretraining a Lite BERT Model for Korean Language Understanding , 2021, 2020 25th International Conference on Pattern Recognition (ICPR).
[13] Nan Duan,et al. Syntax-Enhanced Pre-trained Model , 2020, ACL.
[14] Huanqi Cao,et al. CPM: A Large-scale Generative Chinese Pre-trained Language Model , 2020, AI Open.
[15] Yue Zhang,et al. On Commonsense Cues in BERT for Solving Commonsense Tasks , 2020, FINDINGS.
[16] Li Dong,et al. Self-Attention Attribution: Interpreting Information Interactions Inside Transformer , 2020, AAAI.
[17] Zhiyuan Liu,et al. KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation , 2019, Transactions of the Association for Computational Linguistics.
[18] James Caverlee,et al. Infusing Disease Knowledge into BERT for Health Question Answering, Medical Inference and Disease Name Recognition , 2020, EMNLP.
[19] Zheng Zhang,et al. CoLAKE: Contextualized Language and Knowledge Embedding , 2020, COLING.
[20] Mark Chen,et al. Language Models are Few-Shot Learners , 2020, NeurIPS.
[21] Dian Yu,et al. CLUE: A Chinese Language Understanding Evaluation Benchmark , 2020, COLING.
[22] Wanxiang Che,et al. Revisiting Pre-Trained Models for Chinese Natural Language Processing , 2020, FINDINGS.
[23] Fabio Petroni,et al. How Context Affects Language Models' Factual Predictions , 2020, AKBC.
[24] Hai Zhao,et al. LIMIT-BERT : Linguistic Informed Multi-Task BERT , 2019, ArXiv.
[25] Zhe Zhao,et al. K-BERT: Enabling Language Representation with Knowledge Graph , 2019, AAAI.
[26] Natalia Gimelshein,et al. PyTorch: An Imperative Style, High-Performance Deep Learning Library , 2019, NeurIPS.
[27] Yingming Li,et al. Fine-tune BERT with Sparse Self-Attention Mechanism , 2019, EMNLP.
[28] Noah A. Smith,et al. Knowledge Enhanced Contextual Word Representations , 2019, EMNLP.
[29] Sebastian Riedel,et al. Language Models as Knowledge Bases? , 2019, EMNLP.
[30] Yiming Yang,et al. XLNet: Generalized Autoregressive Pretraining for Language Understanding , 2019, NeurIPS.
[31] Omer Levy,et al. What Does BERT Look at? An Analysis of BERT’s Attention , 2019, BlackboxNLP@ACL.
[32] Maosong Sun,et al. ERNIE: Enhanced Language Representation with Informative Entities , 2019, ACL.
[33] Yu Sun,et al. ERNIE: Enhanced Representation through Knowledge Integration , 2019, ArXiv.
[34] Xiaodong Liu,et al. Multi-Task Deep Neural Networks for Natural Language Understanding , 2019, ACL.
[35] Yiming Yang,et al. Transformer-XL: Attentive Language Models beyond a Fixed-Length Context , 2019, ACL.
[36] Ming-Wei Chang,et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.
[37] Oriol Vinyals,et al. Representation Learning with Contrastive Predictive Coding , 2018, ArXiv.
[38] Omer Levy,et al. GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding , 2018, BlackboxNLP@EMNLP.
[39] Graham Neubig,et al. Neural Lattice Language Models , 2018, TACL.
[40] Yue Zhang,et al. Neural Reranking for Named Entity Recognition , 2017, RANLP.
[41] Bowen Zhou,et al. A Structured Self-attentive Sentence Embedding , 2017, ICLR.
[42] George Kurian,et al. Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation , 2016, ArXiv.
[43] Geoffrey E. Hinton,et al. Layer Normalization , 2016, ArXiv.
[44] Kevin Gimpel,et al. Gaussian Error Linear Units (GELUs) , 2016 .
[45] Nanyun Peng,et al. Named Entity Recognition for Chinese Social Media with Jointly Trained Embeddings , 2015, EMNLP.
[46] Gina-Anne Levow,et al. The Third International Chinese Language Processing Bakeoff: Word Segmentation and Named Entity Recognition , 2006, SIGHAN@COLING/ACL.