Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting最新文献_第2页

Analysis of Behavior Classification in Motivational Interviewing. 动机访谈中的行为分类分析。

Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting Pub Date : 2021-06-01 DOI: 10.18653/v1/2021.clpsych-1.13

Leili Tavabi, Trang Tran, Kalin Stefanov, Brian Borsari, Joshua D Woolley, Stefan Scherer, Mohammad Soleymani

{"title":"Analysis of Behavior Classification in Motivational Interviewing.","authors":"Leili Tavabi, Trang Tran, Kalin Stefanov, Brian Borsari, Joshua D Woolley, Stefan Scherer, Mohammad Soleymani","doi":"10.18653/v1/2021.clpsych-1.13","DOIUrl":"10.18653/v1/2021.clpsych-1.13","url":null,"abstract":"Analysis of client and therapist behavior in counseling sessions can provide helpful insights for assessing the quality of the session and consequently, the client's behavioral outcome. In this paper, we study the automatic classification of standardized behavior codes (i.e. annotations) used for assessment of psychotherapy sessions in Motivational Interviewing (MI). We develop models and examine the classification of client behaviors throughout MI sessions, comparing the performance by models trained on large pretrained embeddings (RoBERTa) versus interpretable and expert-selected features (LIWC). Our best performing model using the pretrained RoBERTa embeddings beats the baseline model, achieving an F1 score of 0.66 in the subject-independent 3-class classification. Through statistical analysis on the classification results, we identify prominent LIWC features that may not have been captured by the model using pretrained embeddings. Although classification using LIWC features underperforms RoBERTa, our findings motivate the future direction of incorporating auxiliary tasks in the classification of MI codes.","PeriodicalId":74542,"journal":{"name":"Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting","volume":"2021 ","pages":"110-115"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321779/pdf/nihms-1727153.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39266882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

TextEssence: A Tool for Interactive Analysis of Semantic Shifts Between Corpora. TextEssence:语料库间语义转换交互分析工具。

Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting Pub Date : 2021-06-01

Denis Newman-Griffis, Venkatesh Sivaraman, Adam Perer, Eric Fosler-Lussier, Harry Hochheiser

引用次数: 0

Translational NLP: A New Paradigm and General Principles for Natural Language Processing Research. 翻译NLP:自然语言处理研究的新范式和一般原则。

Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting Pub Date : 2021-06-01

Denis Newman-Griffis, Jill Fain Lehman, Carolyn Rosé, Harry Hochheiser

{"title":"Translational NLP: A New Paradigm and General Principles for Natural Language Processing Research.","authors":"Denis Newman-Griffis, Jill Fain Lehman, Carolyn Rosé, Harry Hochheiser","doi":"","DOIUrl":"","url":null,"abstract":"Natural language processing (NLP) research combines the study of universal principles, through basic science, with applied science targeting specific use cases and settings. However, the process of exchange between basic NLP and applications is often assumed to emerge naturally, resulting in many innovations going unapplied and many important questions left unstudied. We describe a new paradigm of Translational NLP, which aims to structure and facilitate the processes by which basic and applied NLP research inform one another. Translational NLP thus presents a third research paradigm, focused on understanding the challenges posed by application needs and how these challenges can drive innovation in basic science and technology design. We show that many significant advances in NLP research have emerged from the intersection of basic principles with application needs, and present a conceptual framework outlining the stakeholders and key questions in translational research. Our framework provides a roadmap for developing Translational NLP as a dedicated research area, and identifies general translational principles to facilitate exchange between basic and applied research.","PeriodicalId":74542,"journal":{"name":"Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting","volume":"2021 ","pages":"4125-4138"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8223521/pdf/nihms-1710048.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39115253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Empirical Evaluation of Pre-trained Transformers for Human-Level NLP: The Role of Sample Size and Dimensionality. 对人类水平NLP的预训练变压器的经验评价:样本大小和维度的作用。

Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting Pub Date : 2021-06-01 DOI: 10.18653/v1/2021.naacl-main.357

Adithya V Ganesan, Matthew Matero, Aravind Reddy Ravula, Huy Vu, H Andrew Schwartz

{"title":"Empirical Evaluation of Pre-trained Transformers for Human-Level NLP: The Role of Sample Size and Dimensionality.","authors":"Adithya V Ganesan, Matthew Matero, Aravind Reddy Ravula, Huy Vu, H Andrew Schwartz","doi":"10.18653/v1/2021.naacl-main.357","DOIUrl":"https://doi.org/10.18653/v1/2021.naacl-main.357","url":null,"abstract":"In human-level NLP tasks, such as predicting mental health, personality, or demographics, the number of observations is often smaller than the standard 768+ hidden state sizes of each layer within modern transformer-based language models, limiting the ability to effectively leverage transformers. Here, we provide a systematic study on the role of dimension reduction methods (principal components analysis, factorization techniques, or multi-layer auto-encoders) as well as the dimensionality of embedding vectors and sample sizes as a function of predictive performance. We first find that fine-tuning large models with a limited amount of data pose a significant difficulty which can be overcome with a pre-trained dimension reduction regime. RoBERTa consistently achieves top performance in human-level tasks, with PCA giving benefit over other reduction methods in better handling users that write longer texts. Finally, we observe that a majority of the tasks achieve results comparable to the best performance with just <math> <mrow><mfrac><mn>1</mn> <mrow><mn>12</mn></mrow> </mfrac> </mrow> </math> of the embedding dimensions.","PeriodicalId":74542,"journal":{"name":"Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting","volume":"2021 ","pages":"4515-4532"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8294338/pdf/nihms-1716243.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39215546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 20

What's in a Summary? Laying the Groundwork for Advances in Hospital-Course Summarization. 摘要有哪些内容？为医院课程总结的进步奠定基础。

Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting Pub Date : 2021-06-01 DOI: 10.18653/v1/2021.naacl-main.382

Griffin Adams, Emily Alsentzer, Mert Ketenci, Jason Zucker, Noémie Elhadad

引用次数: 0

Word centrality constrained representation for keyphrase extraction. 关键词提取的词中心性约束表示。

Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting Pub Date : 2021-06-01 DOI: 10.18653/v1/2021.bionlp-1.17

Zelalem Gero, Joyce C Ho

引用次数: 5

Translational NLP: A New Paradigm and General Principles for Natural Language Processing Research 翻译NLP:自然语言处理研究的新范式和一般原则

Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting Pub Date : 2021-04-16 DOI: 10.18653/V1/2021.NAACL-MAIN.325

Denis Newman-Griffis, J. Lehman, C. Ros'e, H. Hochheiser

{"title":"Translational NLP: A New Paradigm and General Principles for Natural Language Processing Research","authors":"Denis Newman-Griffis, J. Lehman, C. Ros'e, H. Hochheiser","doi":"10.18653/V1/2021.NAACL-MAIN.325","DOIUrl":"https://doi.org/10.18653/V1/2021.NAACL-MAIN.325","url":null,"abstract":"Natural language processing (NLP) research combines the study of universal principles, through basic science, with applied science targeting specific use cases and settings. However, the process of exchange between basic NLP and applications is often assumed to emerge naturally, resulting in many innovations going unapplied and many important questions left unstudied. We describe a new paradigm of Translational NLP, which aims to structure and facilitate the processes by which basic and applied NLP research inform one another. Translational NLP thus presents a third research paradigm, focused on understanding the challenges posed by application needs and how these challenges can drive innovation in basic science and technology design. We show that many significant advances in NLP research have emerged from the intersection of basic principles with application needs, and present a conceptual framework outlining the stakeholders and key questions in translational research. Our framework provides a roadmap for developing Translational NLP as a dedicated research area, and identifies general translational principles to facilitate exchange between basic and applied research.","PeriodicalId":74542,"journal":{"name":"Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting","volume":"21 1","pages":"4125-4138"},"PeriodicalIF":0.0,"publicationDate":"2021-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86528175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Paragraph-level Simplification of Medical Texts 医学文本的分段简化

Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting Pub Date : 2021-04-12 DOI: 10.18653/V1/2021.NAACL-MAIN.395

Ashwin Devaraj, I. Marshall, Byron C. Wallace, J. Li

{"title":"Paragraph-level Simplification of Medical Texts","authors":"Ashwin Devaraj, I. Marshall, Byron C. Wallace, J. Li","doi":"10.18653/V1/2021.NAACL-MAIN.395","DOIUrl":"https://doi.org/10.18653/V1/2021.NAACL-MAIN.395","url":null,"abstract":"We consider the problem of learning to simplify medical texts. This is important because most reliable, up-to-date information in biomedicine is dense with jargon and thus practically inaccessible to the lay audience. Furthermore, manual simplification does not scale to the rapidly growing body of biomedical literature, motivating the need for automated approaches. Unfortunately, there are no large-scale resources available for this task. In this work we introduce a new corpus of parallel texts in English comprising technical and lay summaries of all published evidence pertaining to different clinical topics. We then propose a new metric based on likelihood scores from a masked language model pretrained on scientific texts. We show that this automated measure better differentiates between technical and lay summaries than existing heuristics. We introduce and evaluate baseline encoder-decoder Transformer models for simplification and propose a novel augmentation to these in which we explicitly penalize the decoder for producing “jargon” terms; we find that this yields improvements over baselines in terms of readability.","PeriodicalId":74542,"journal":{"name":"Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting","volume":"7 1","pages":"4972-4984"},"PeriodicalIF":0.0,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78695199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 47

TextEssence: A Tool for Interactive Analysis of Semantic Shifts Between Corpora TextEssence:语料库间语义转换交互分析工具

Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting Pub Date : 2021-03-19 DOI: 10.18653/v1/2021.naacl-demos.13

Denis Newman-Griffis, Venkatesh Sivaraman, Adam Perer, E. Fosler-Lussier, H. Hochheiser

引用次数: 1

Trialstreamer: Mapping and Browsing Medical Evidence in Real-Time. Trialstreamer:实时绘制和浏览医学证据。

Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting Pub Date : 2020-07-01 DOI: 10.18653/v1/2020.acl-demos.9

Benjamin E Nye, Ani Nenkova, Iain J Marshall, Byron C Wallace

{"title":"Trialstreamer: Mapping and Browsing Medical Evidence in Real-Time.","authors":"Benjamin E Nye, Ani Nenkova, Iain J Marshall, Byron C Wallace","doi":"10.18653/v1/2020.acl-demos.9","DOIUrl":"https://doi.org/10.18653/v1/2020.acl-demos.9","url":null,"abstract":"We introduce Trialstreamer, a living database of clinical trial reports. Here we mainly describe the evidence extraction component; this extracts from biomedical abstracts key pieces of information that clinicians need when appraising the literature, and also the relations between these. Specifically, the system extracts descriptions of trial participants, the treatments compared in each arm (the interventions), and which outcomes were measured. The system then attempts to infer which interventions were reported to work best by determining their relationship with identified trial outcome measures. In addition to summarizing individual trials, these extracted data elements allow automatic synthesis of results across many trials on the same topic. We apply the system at scale to all reports of randomized controlled trials indexed in MEDLINE, powering the automatic generation of evidence maps, which provide a global view of the efficacy of different interventions combining data from all relevant clinical trials on a topic. We make all code and models freely available alongside a demonstration of the web interface.","PeriodicalId":74542,"journal":{"name":"Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting","volume":"2020 ","pages":"63-69"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8204713/pdf/nihms-1593346.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39239461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 20