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In this research, we utilized the training dataset from the ROCLING 2023 Chinese Multi-genre Named Entity Recognition in the Healthcare Domain, which comprises the Chi- nese HealthNER Corpus (Lee and Lu, 2021) and the ROCLING 2022 CHNER Dataset (Lee et al., 2022), along with the test set (Lee et al., …...

This paper describes the ROCLING-2023 shared task for Chinese multi-genre named entity recognition in the healthcare domain, including task description, data preparation, performance metrics, and evaluation results. Among eight registered teams, six participating teams submitted a total of 16 runs. This shared task demonstrates current NLP techniques for dealing with …...

Medical Named Entity Recognition (NER) stands as a pivotal technique within the realm of medicine, cate sequence labeling.encompassing intri- Profound medi- cal knowledge acumen and accurate de- marcation of entity boundaries constitute the principal challenges of this task. In contrast to the English context, Chinese medical NER poses even greater …...

AbstractThis paper illustrates a new methodology based on Test Suites (Avramidis et al., 2018) with focus on Business Critical Errors (BCEs) (Stewart et al., 2022) to evaluate the output of Machine Translation (MT) and Quality Estimation (QE) systems. We demonstrate the value of relying on semi-automatic evaluation done through scalable …...

In this study, the speech recognition sys- tem will be introduced, used by NSYSU- MITLab, for Formosa Speech Recogni- tion Challenge 2023. We use the pre- trained model wav2vec2.0 as the frontend module in both the Enhanced Branch- former system and the Dynamic convolu- tion Enhanced Branchformer system. The Dynamic …...

Zhangzhou Southern Min is theoretically assumed to have 7320 possible syllables but more than 70% of them are not attested in the empirical data, implying that substantial constraints have been governing the segmental sequencing and segmental-suprasegmental alignment. This study explores phonotactic constraints on syllable onsets. It addresses two important issues …...

Chinese healthcare NER is an essential task in natural language processing to automatically identify healthcare entities such as symptoms, chemicals, diseases, and treatments for machine reading and understanding. Previous studies used Bi-directional Long Short-Term Memory (BiLSTM) and Conditional Random Fields (CRF) to solve NER tasks. This paper uses the RoBERTa-large …...

The demand for sequence segmentation and tagging has recently extended to different professional fields. The most commonly used model in conventional solutions is Bidirectional Long Short-Term Memory-Conditional Random Fields (Bi- LSTM-CRF), which combines deep learning and supervised learning. As the importance of unsupervised learning has become equal to that of …...

In this research, we comprehensively ana- lyze the potential biases inherent in Large Language Model, utilizing meticulously cu- rated input data to ascertain the extent to which such data sway machine-generated responses to yield prejudiced outcomes. Notwithstanding recent strides in mitigat- ing bias in LLM-based NLP, our findings underscore the …...

Lexical complexity is crucial for reading comprehension. In the past, research work of lexical complexity prediction mainly focuses on differentiating the complexity difference between two words. Moreover, most of the previous lexical complexity prediction approaches only consider traditional lexically relevant features. In this paper, we propose a novel supervised approach …...

In this study, we delve into the efficacy of the Tree-of-Thought Prompting technique as a mechanism to address linguistic challenges and augment the reasoning capabilities of expansive language models. Specifically, we scrutinize the reasoning prowess of the Generative Pre-trained Transformer (GPT) model, which has garnered significant at- tention within the …...

According to data from the World Meteorological Organization, the temperature on Earth has risen by nearly 1°C from 1850 to 2020, causing global climate anomalies and seriously affecting the melting of Antarctic ice and Greenland ice. In the next 100 years, if the ice completely melts, the sea level will …...

While argument mining has garnered attention over the years, its application in the financial sector remains nascent. This study presents a BERT-based ensemble learning approach tailored for sentiment analysis grounded in financial narratives, specifically focusing on unearthing arguments. For a nuanced analysis, we dissect the challenge into two pivotal subtasks …...

In this paper, we explore compact convolutional neural networks (CNNs) for end-to-end key- word spotting from raw audio to final recogni- tion results, without using traditional feature extraction based on spectrogram. Such fully CNN models reach 90.5% accuracy, an im- provement of 12.15% over traditional meth- ods with similar structures, …...

AbstractThis work proposes an approach to use Part-Of-Speech (POS) information to automatically detect context-dependent Translation Units (TUs) from a Translation Memory database pertaining to the customer support domain. In line with our goal to minimize context-dependency in TUs, we show how this mechanism can be deployed to create new gender-neutral …...

Contemporary large language mod- els (LLMs) have made significant advancements, capable of generating fluent conversations with humans and accomplishing various tasks such as programming and question answering (QA). Nevertheless, current LLMs are still faced with numerous challenges, including generating hallucinations, lacking the latest information, suffering from biases, and others. In …...

Automatic generation of questions about the given context is useful for the adaptation of question-answering systems or to support edu- cation. We trained and evaluated a model that generates a question in the Slovak language. We have designed an automatic metric where an additional question-answering model is used to evaluate …...

The objective of Sentence-level Revision (SentRev) is to enhance the fluency of En- glish writing; however, the performance of the three baseline methods is notably suboptimal. In this study, we propose a method utilizing neural reinforcement learning, tailored to the specific character- istics of this task, which has resulted in …...

In this study, we assess ChatGPT, OpenAI’s latest conversational chatbot and large lan- guage model (LLM), on its performance in elementary-grade arithmetic and logic prob- lems. Despite its impressive coherence in nat- ural language processing and ability to follow instructions, our findings indicate that Chat- GPT still has room for …...

This paper introduces the Cross-lingual Fact Extraction and VERification (XFEVER) dataset designed for benchmarking the fact ver- ification models across different languages. We constructed it by translating the claim and ev- idence texts of the Fact Extraction and VERi- fication (FEVER) dataset released by Thorne et al. (2018) into six …...