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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; Meyer, Francois; Oortwijn, Yvette; Sommerauer, Pia; Zhou, Wei. - : Underline Science Inc., 2021 Abstract: Read the paper on the folowing link: https://www.aclweb.org/anthology/2021.naacl-main.199/ Abstract: Computational linguistic research on language change through distributional semantic (DS) models has inspired researchers from fields such as philosophy and literary studies, who use these methods for the exploration and comparison of comparatively small datasets traditionally analyzed by close reading. Research on methods for small data is still in early stages and it is not clear which methods achieve the best results. We investigate the possibilities and limitations of using distributional semantic models for analyzing philosophical data by means of a realistic use-case. We provide a ground truth for evaluation created by philosophy experts and a blueprint for using DS models in a sound methodological setup. We compare three methods for creating specialized models from small datasets. Though the models do not perform well enough to directly support philosophers yet, we find that models designed for small ... Keyword: Artificial Intelligence; Computer Science and Engineering; Intelligent System; Natural Language Processing URL: https://dx.doi.org/10.48448/mzvd-3v98 https://underline.io/lecture/20012-challenging-distributional-models-with-a-conceptual-network-of-philosophical-terms BASE Hide details 16 Modeling the Severity of Complaints in Social Media ... NAACL 2021 2021; Aletras, Nikolaos; Jin, Mali. - : Underline Science Inc., 2021 BASE Show 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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