Search Results for author: Leyang Cui

Found 19 papers, 14 papers with code

FactMix: Using a Few Labeled In-domain Examples to Generalize to Cross-domain Named Entity Recognition

1 code implementation24 Aug 2022 Linyi Yang, Lifan Yuan, Leyang Cui, Wenyang Gao, Yue Zhang

Few-shot Named Entity Recognition (NER) is imperative for entity tagging in limited resource domains and thus received proper attention in recent years.

Cross-Domain Named Entity Recognition Data Augmentation +4

Effidit: Your AI Writing Assistant

no code implementations3 Aug 2022 Shuming Shi, Enbo Zhao, Duyu Tang, Yan Wang, Piji Li, Wei Bi, Haiyun Jiang, Guoping Huang, Leyang Cui, Xinting Huang, Cong Zhou, Yong Dai, Dongyang Ma

In Effidit, we significantly expand the capacities of a writing assistant by providing functions in five categories: text completion, error checking, text polishing, keywords to sentences (K2S), and cloud input methods (cloud IME).

Keywords to Sentences Sentence Completion +1

Towards Robust Online Dialogue Response Generation

no code implementations7 Mar 2022 Leyang Cui, Fandong Meng, Yijin Liu, Jie zhou, Yue Zhang

Although pre-trained sequence-to-sequence models have achieved great success in dialogue response generation, chatbots still suffer from generating inconsistent responses in real-world practice, especially in multi-turn settings.

Chatbot Re-Ranking +1

Do Prompts Solve NLP Tasks Using Natural Language?

no code implementations2 Mar 2022 Sen yang, Yunchen Zhang, Leyang Cui, Yue Zhang

Thanks to the advanced improvement of large pre-trained language models, prompt-based fine-tuning is shown to be effective on a variety of downstream tasks.

Investigating Non-local Features for Neural Constituency Parsing

1 code implementation ACL 2022 Leyang Cui, Sen yang, Yue Zhang

Besides, our method achieves state-of-the-art BERT-based performance on PTB (95. 92 F1) and strong performance on CTB (92. 31 F1).

Constituency Parsing

Knowledge Enhanced Fine-Tuning for Better Handling Unseen Entities in Dialogue Generation

1 code implementation EMNLP 2021 Leyang Cui, Yu Wu, Shujie Liu, Yue Zhang

To deal with this problem, instead of introducing knowledge base as the input, we force the model to learn a better semantic representation by predicting the information in the knowledge base, only based on the input context.

Dialogue Generation

Template-Based Named Entity Recognition Using BART

1 code implementation Findings (ACL) 2021 Leyang Cui, Yu Wu, Jian Liu, Sen yang, Yue Zhang

To address the issue, we propose a template-based method for NER, treating NER as a language model ranking problem in a sequence-to-sequence framework, where original sentences and statement templates filled by candidate named entity span are regarded as the source sequence and the target sequence, respectively.

few-shot-ner Few-shot NER +4

Natural Language Inference in Context -- Investigating Contextual Reasoning over Long Texts

1 code implementation10 Nov 2020 Hanmeng Liu, Leyang Cui, Jian Liu, Yue Zhang

Natural language inference (NLI) is a fundamental NLP task, investigating the entailment relationship between two texts.

Logical Reasoning Natural Language Inference

Does Chinese BERT Encode Word Structure?

1 code implementation COLING 2020 Yile Wang, Leyang Cui, Yue Zhang

Contextualized representations give significantly improved results for a wide range of NLP tasks.

Chunking Natural Language Inference +1

What Have We Achieved on Text Summarization?

1 code implementation EMNLP 2020 Dandan Huang, Leyang Cui, Sen yang, Guangsheng Bao, Kun Wang, Jun Xie, Yue Zhang

Deep learning has led to significant improvement in text summarization with various methods investigated and improved ROUGE scores reported over the years.

Text Summarization

On Commonsense Cues in BERT for Solving Commonsense Tasks

no code implementations Findings (ACL) 2021 Leyang Cui, Sijie Cheng, Yu Wu, Yue Zhang

We quantitatively investigate the presence of structural commonsense cues in BERT when solving commonsense tasks, and the importance of such cues for the model prediction.

Sentiment Analysis

LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

1 code implementation16 Jul 2020 Jian Liu, Leyang Cui, Hanmeng Liu, Dandan Huang, Yile Wang, Yue Zhang

Machine reading is a fundamental task for testing the capability of natural language understanding, which is closely related to human cognition in many aspects.

Logical Reasoning Machine Reading Comprehension +1

MuTual: A Dataset for Multi-Turn Dialogue Reasoning

1 code implementation ACL 2020 Leyang Cui, Yu Wu, Shujie Liu, Yue Zhang, Ming Zhou

Non-task oriented dialogue systems have achieved great success in recent years due to largely accessible conversation data and the development of deep learning techniques.

Task-Oriented Dialogue Systems

Evaluating Commonsense in Pre-trained Language Models

1 code implementation27 Nov 2019 Xuhui Zhou, Yue Zhang, Leyang Cui, Dandan Huang

However, relatively little work has been done investigating commonsense knowledge contained in contextualized representations, which is crucial for human question answering and reading comprehension.

Language Modelling Question Answering +1

How Can BERT Help Lexical Semantics Tasks?

no code implementations7 Nov 2019 Yile Wang, Leyang Cui, Yue Zhang

Contextualized embeddings such as BERT can serve as strong input representations to NLP tasks, outperforming their static embeddings counterparts such as skip-gram, CBOW and GloVe.

Word Embeddings

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