Natural-language-understanding-papers
A list of recent papers regarding natural language understanding and spoken language understanding.
It covers different semantic representations:
- domain-intent-slot;
- SQL query;
Bookmarks
- NLU papers for domain-intent-slot
- NLU papers for text2SQL
- Universal Language Representation
- Which may inspire us
1 NLU papers for domain-intent-slot
- Please see the paper list.
2 NLU papers for text2SQL
- Please see the paper list.
3 Universal Language Representation
- Deep contextualized word representations. Matthew E. Peters, et al. NAACL 2018. [ELMo]
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Jacob Devlin, et al. NAACL 2019. [from Google AI Language]
- XLNet: Generalized Autoregressive Pretraining for Language Understanding. Zhilin Yang, et al. Arxiv 2019. [CMU && Google Brain]
4 Which may inspire us
- Jointly Predicting Predicates and Arguments in Neural Semantic Role Labeling. Luheng He, et al. ACL, 2018. [Code]
- Sentence-State LSTM for Text Representation. Yue Zhang, et al. ACL, 2018. [Code]
- Chinese NER Using Lattice LSTM. Yue Zhang, et al. ACL, 2018. [Code+data]
- SoPa: Bridging CNNs, RNNs, and Weighted Finite-State Machines. Roy Schwartz, et al. ACL, 2018. [Code]
- Coarse-to-Fine Decoding for Neural Semantic Parsing. Li Dong and Mirella Lapata. ACL, 2018. [Code]
- Generalize Symbolic Knowledge With Neural Rule Engine. Shen Li, Hengru Xu, Zhengdong Lu. Arxiv 2018. [from Deeplycurious.ai]
- Dual Supervised Learning for Natural Language Understanding and Generation. Shang-Yu Su, et al. ACL, 2019.
- Neural Finite State Transducers: Beyond Rational Relations. Chu-Cheng Lin, et al. NAACL, 2019.
- Paper lists of Meta learning for NLP.