A Scoping Literature Review of Natural Language Processing Application to Safety Occurrence Reports
Safety, 2023 Safety occurrence reports can contain valuable information on how incidents occur, revealing knowledge that can assist safety practitioners. This paper presents and discusses a literature review exploring how Natural Language Processing (NLP) has been ...
John W. Ricketts +3 more
semanticscholar +1 more source
Is Reinforcement Learning (Not) for Natural Language Processing?: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization [PDF]
arXiv.org, 2022 We tackle the problem of aligning pre-trained large language models (LMs) with human preferences. If we view text generation as a sequential decision-making problem, reinforcement learning (RL) appears to be a natural conceptual framework. However, using
Rajkumar Ramamurthy +7 more
semanticscholar +1 more source
The Stanford CoreNLP Natural Language Processing Toolkit
Annual Meeting of the Association for Computational Linguistics, 2014 We describe the design and use of the Stanford CoreNLP toolkit, an extensible pipeline that provides core natural language analysis. This toolkit is quite widely used, both in the research NLP community and also among commercial and government users of ...
Christopher D. Manning +5 more
semanticscholar +1 more source
AllenNLP: A Deep Semantic Natural Language Processing Platform [PDF]
arXiv.org, 2018 Modern natural language processing (NLP) research requires writing code. Ideally this code would provide a precise definition of the approach, easy repeatability of results, and a basis for extending the research.
Matt Gardner +8 more
semanticscholar +1 more source
PyThaiNLP: Thai Natural Language Processing in Python [PDF]
NLPOSS, 2023 We present PyThaiNLP, a free and open-source natural language processing (NLP) library for Thai language implemented in Python. It provides a wide range of software, models, and datasets for Thai language.
Wannaphong Phatthiyaphaibun +8 more
semanticscholar +1 more source
Applied Sciences, 2023 The development of conversational agents that can generate relevant and meaningful replies is a challenging task in the field of natural language processing.
Quoc-Dai Luong Tran, Anh-Cuong Le
doaj +1 more source
Unlocking the Potential of ChatGPT: A Comprehensive Exploration of its Applications, Advantages, Limitations, and Future Directions in Natural Language Processing [PDF]
arXiv.org, 2023 Large language models, pivotal in artificial intelligence, find diverse applications. ChatGPT (Chat Generative Pre-trained Transformer), an OpenAI creation, stands out as a widely adopted, powerful tool.
Walid Hariri
semanticscholar +1 more source
Research on sentence alignment based on modeling word pairs [PDF]
Jisuanji gongcheng, 2019 Sentence alignment is a process mapping sentences in the source text to their counterparts in the target text.Within the framework of neural network,this paper proposes a sentence alignment method,on the basis that the aligned source sentence and target ...
DING Ying,LI Junhui,ZHOU Guodong
doaj +1 more source
An Efficient Deep Learning for Thai Sentiment Analysis
Data, 2023 The number of reviews from customers on travel websites and platforms is quickly increasing. They provide people with the ability to write reviews about their experience with respect to service quality, location, room, and cleanliness, thereby helping ...
Nattawat Khamphakdee +1 more
doaj +1 more source
A Survey of the Usages of Deep Learning for Natural Language Processing
IEEE Transactions on Neural Networks and Learning Systems, 2020 Over the last several years, the field of natural language processing has been propelled forward by an explosion in the use of deep learning models.
Dan Otter, Julian R. Medina, J. Kalita
semanticscholar +1 more source