Named Entity Recognition with Bidirectional LSTM-CNNs [PDF]
Transactions of the Association for Computational Linguistics, 2015 Named entity recognition is a challenging task that has traditionally required large amounts of knowledge in the form of feature engineering and lexicons to achieve high performance.
Jason P. C. Chiu, Eric Nichols
semanticscholar +1 more source
GoEmotions: A Dataset of Fine-Grained Emotions [PDF]
Annual Meeting of the Association for Computational Linguistics, 2020 Understanding emotion expressed in language has a wide range of applications, from building empathetic chatbots to detecting harmful online behavior.
Dorottya Demszky +5 more
semanticscholar +1 more source
Scientific Reports, 2023 The segmentation of acute stroke lesions plays a vital role in healthcare by assisting doctors in making prompt and well-informed treatment choices. Although Magnetic Resonance Imaging (MRI) is a time-intensive procedure, it produces high-fidelity images
Parisa Soleimani, Navid Farezi
doaj +1 more source
A Tale of Two Cultures: Comparing Interpersonal Information Disclosure Norms on Twitter [PDF]
, 2023 We present an exploration of cultural norms surrounding online disclosure of information about one's interpersonal relationships (such as information about family members, colleagues, friends, or lovers) on Twitter. The literature identifies the cultural dimension of individualism versus collectivism as being a major determinant of offline ...
arxiv +1 more source
Sampling Frequency Evaluation on Recurrent Neural Networks Architectures for IoT Real-time Fall Detection Devices [PDF]
, 2019 Falls are one of the most frequent causes of injuries in elderly people. Wearable Fall Detection Systems provided a ubiquitous tool for monitoring and alert when these events happen.
Amaya Rodríguez, Isabel +9 more
core +1 more source
Xu at SemEval-2022 Task 4: Pre-BERT Neural Network Methods vs Post-BERT RoBERTa Approach for Patronizing and Condescending Language Detection [PDF]
arXiv, 2022 This paper describes my participation in the SemEval-2022 Task 4: Patronizing and Condescending Language Detection. I participate in both subtasks: Patronizing and Condescending Language (PCL) Identification and Patronizing and Condescending Language Categorization, with the main focus put on subtask 1.
arxiv
Adversarial Examples for Evaluating Reading Comprehension Systems [PDF]
Conference on Empirical Methods in Natural Language Processing, 2017 Standard accuracy metrics indicate that reading comprehension systems are making rapid progress, but the extent to which these systems truly understand language remains unclear.
Robin Jia, Percy Liang
semanticscholar +1 more source
VirSorter2: a multi-classifier, expert-guided approach to detect diverse DNA and RNA viruses
Microbiome, 2021 Viruses are a significant player in many biosphere and human ecosystems, but most signals remain “hidden” in metagenomic/metatranscriptomic sequence datasets due to the lack of universal gene markers, database representatives, and insufficiently advanced
Jiarong Guo +10 more
semanticscholar +1 more source
CoQA: A Conversational Question Answering Challenge [PDF]
Transactions of the Association for Computational Linguistics, 2018 Humans gather information through conversations involving a series of interconnected questions and answers. For machines to assist in information gathering, it is therefore essential to enable them to answer conversational questions. We introduce CoQA, a
Siva Reddy +2 more
semanticscholar +1 more source
LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype [PDF]
arXiv, 2023 The accurate classification of lymphoma subtypes using hematoxylin and eosin (H&E)-stained tissue is complicated by the wide range of morphological features these cancers can exhibit. We present LymphoML - an interpretable machine learning method that identifies morphologic features that correlate with lymphoma subtypes.
arxiv