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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 6 Hits 1 – 20 of 115 1 Negative language transfer in learner English: A new dataset ... NAACL 2021 2021; Demmans Epp, Carrie; Farias Wanderley, Leticia. - : Underline Science Inc., 2021 BASE Show details 2 Generative Imagination Elevates Machine Translation ... NAACL 2021 2021; Li, Lei; Long, Quanyu. - : Underline Science Inc., 2021 BASE Show details 3 Parallel sentences mining with transfer learning in an unsupervised setting ... NAACL 2021 2021; Feng, Yifan; Mi, Chenggang. - : Underline Science Inc., 2021 BASE Show details 4 Source and Target Bidirectional Knowledge Distillation for End-to-end Speech Translation ... NAACL 2021 2021; Inaguma, Hirofumi. - : Underline Science Inc., 2021 BASE Show details 5 Detoxifying Language Models Risks Marginalizing Minority Voices ... NAACL 2021 2021; Gururangan, Suchin; Klein, Dan. - : Underline Science Inc., 2021 BASE Show details 6 Domain Adaptation for Arabic Cross-Domain and Cross-Dialect Sentiment Analysis from Contextualized Word Embedding ... NAACL 2021 2021; Berrada, Ismail; El Mahdaouy, Abdelkader. - : Underline Science Inc., 2021 BASE Show details 7 Knowledge Enhanced Masked Language Model for Stance Detection ... NAACL 2021 2021; Kawintiranon, Kornraphop; Singh, Lisa. - : Underline Science Inc., 2021 BASE Show details 8 LIVE SESSION: 15D-Oral: Phonology, Morphology and Word Segmentation ... NAACL 2021 2021. - : Underline Science Inc., 2021 BASE Show details 9 Universal Dependencies ... NAACL 2021 2021; de Marneffe, Marie-Catherine; Manning, Christopher. - : Underline Science Inc., 2021 BASE Show details 10 How low is too low? A monolingual take on lemmatisation in Indian languages ... NAACL 2021 2021; Bhattacharyya, Pushpak; Saunack, Kumar. - : Underline Science Inc., 2021 BASE Show details 11 Frustratingly Easy Edit-based Linguistic Steganography with a Masked Language Model ... NAACL 2021 2021; Kurohashi, Sadao; Murawaki, Yugo. - : Underline Science Inc., 2021 BASE Show details 12 MelBERT: Metaphor Detection via Contextualized Late Interaction using Metaphorical Identification Theories ... NAACL 2021 2021; Choi, Minjin; Choi, Eunseong. - : Underline Science Inc., 2021 BASE Show details 13 A Global Past-Future Early Exit Method for Accelerating Inference of Pre-trained Language Models ... NAACL 2021 2021; He, Bin; Liao, Kaiyuan. - : Underline Science Inc., 2021 BASE Show details 14 DirectProbe: Studying Representations without Classifiers ... NAACL 2021 2021; Srikumar, Vivek; Zhou, Yichu. - : Underline Science Inc., 2021 BASE Show details 15 Challenging distributional models with a conceptual network of philosophical terms ... NAACL 2021 2021; Bloem, Jelke; Fokkens, Antske. - : Underline Science Inc., 2021 BASE Show details 16 Modeling the Severity of Complaints in Social Media ... NAACL 2021 2021; Aletras, Nikolaos; Jin, Mali. - : Underline Science Inc., 2021 Abstract: Read the paper on the folowing link: https://www.aclweb.org/anthology/2021.naacl-main.180/ Abstract: The speech act of complaining is used by humans to communicate a negative mismatch between reality and expectations as a reaction to an unfavorable situation. Linguistic theory of pragmatics categorizes complaints into various severity levels based on the face-threat that the complainer is willing to undertake. This is particularly useful for understanding the intent of complainers and how humans develop suitable apology strategies. In this paper, we study the severity level of complaints for the first time in computational linguistics. To facilitate this, we enrich a publicly available data set of complaints with four severity categories and train different transformer-based networks combined with linguistic information achieving 55.7 macro F1. We also jointly model binary complaint classification and complaint severity in a multi-task setting achieving new state-of-the-art results on binary complaint ... Keyword: Artificial Intelligence; Computer Science and Engineering; Intelligent System; Natural Language Processing URL: https://dx.doi.org/10.48448/ghjc-1t03 https://underline.io/lecture/19992-modeling-the-severity-of-complaints-in-social-media BASE Hide details 17 ERNIE-Gram: Pre-Training with Explicitly N-Gram Masked Language Modeling for Natural Language Understanding ... NAACL 2021 2021; Li, Yu-Kun; Xiao, Dongling. - : Underline Science Inc., 2021 BASE Show details 18 Proteno: Text Normalization with Limited Data for Fast Deployment in Text to Speech Systems ... NAACL 2021 2021; Tyagi, Shubhi. - : Underline Science Inc., 2021 BASE Show details 19 CaSiNo: A Corpus of Campsite Negotiation Dialogues for Automatic Negotiation Systems ... NAACL 2021 2021; Chawla, Kushal; Clever, Rene. - : Underline Science Inc., 2021 BASE Show details 20 multiPRover: Generating Multiple Proofs for Improved Interpretability in Rule Reasoning ... NAACL 2021 2021; Bansal, Mohit; Saha, Swarnadeep. - : Underline Science Inc., 2021 BASE Show details Page: 1 2 3 4 5 6

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