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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...16 Hits 1 – 20 of 307 1 Le modèle Transformer: un « couteau suisse » pour le traitement automatique des langues Yvon, François In: Techniques de l'Ingenieur ; https://hal.archives-ouvertes.fr/hal-03619077 ; Techniques de l'Ingenieur, Techniques de l'ingénieur, 2022, ⟨10.51257/a-v1-in195⟩ ; https://www.techniques-ingenieur.fr/base-documentaire/innovation-th10/innovations-en-electronique-et-tic-42257210/transformer-des-reseaux-de-neurones-pour-le-traitement-automatique-des-langues-in195/ (2022) BASE Show details 2 Structured, flexible, and robust: comparing linguistic plans and explanations generated by humans and large language models ... Wei, Megan. - : Open Science Framework, 2022 Abstract: How much can be learned about the structure of thinking from the statistics of language alone? Large language models -- neural models trained on next-word prediction tasks over large corpuses of text -- have made striking advances in modeling the statistical distribution of language. Sufficiently large corpuses contain language in which humans describe their beliefs and intentions, their goals and plans, and their stories about occurrences in real and imaginary worlds. Richly structured cognitive processes underlie this language that we produce; however, can such structure be captured when modeling distributional co-occurance of words alone? Is language modeling alone sufficiently flexible, accurate, and robust enough to generate language for novel, out-of-distribution queries, or are model-based approaches needed? In this study, we compare human and large-language-model performance on two domains which draw on structured, model-based thinking: 1) goal-based planning, and 2) explanation generation for causal ... Keyword: Artificial Intelligence and Robotics; Computer Sciences; GPT-3; Language Models; Natural Language Processing; Physical Sciences and Mathematics; Planning URL: https://dx.doi.org/10.17605/osf.io/cy72b https://osf.io/cy72b/ BASE Hide details 3 Easy-to-use combination of POS and BERT model for domain-specific and misspelled terms Benamar, Alexandra; Bothua, Meryl; Grouin, Cyril... In: NL4IA Workshop Proceedings ; https://hal.archives-ouvertes.fr/hal-03474696 ; NL4IA Workshop Proceedings, Nov 2021, Milan, Italy (2021) BASE Show details 4 Globalizing BERT-based Transformer Architectures for Long DocumentSummarization Grail, Quentin; Perez, Julien; Gaussier, Éric In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume ; 16th Conference of the European Chapter of the Association for Computational Linguistics ; https://hal.univ-grenoble-alpes.fr/hal-03367913 ; 16th Conference of the European Chapter of the Association for Computational Linguistics, Association for Computational Linguistics, Apr 2021, Online, France (2021) BASE Show details 5 Automatic Error Type Annotation for Arabic ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Belkebir, Riadh; Habash, Nizar. - : Underline Science Inc., 2021 BASE Show details 6 Navigating the Kaleidoscope of COVID-19 Misinformation Using Deep Learning ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Chen, Yuanzhi; Hasan, Mohammad. - : Underline Science Inc., 2021 BASE Show details 7 HittER: Hierarchical Transformers for Knowledge Graph Embeddings ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Chen, Sanxing; Gao, Jianfeng. - : Underline Science Inc., 2021 BASE Show details 8 Detecting Gender Bias using Explainability ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Krithika; Gupta, Gauri. - : Underline Science Inc., 2021 BASE Show details 9 HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; He, Lifang; LIU, YE. - : Underline Science Inc., 2021 BASE Show details 10 Not All Negatives are Equal: Label-Aware Contrastive Loss for Fine-grained Text Classification ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ong, Desmond; Suresh, Varsha. - : Underline Science Inc., 2021 BASE Show details 11 Contrastive Code Representation Learning ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Jain, Ajay; Jain, Paras. - : Underline Science Inc., 2021 BASE Show details 12 Unsupervised Multi-View Post-OCR Error Correction With Language Models ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Brenner, Eliot; Broscheit, Samuel. - : Underline Science Inc., 2021 BASE Show details 13 AttentionRank: Unsupervised Keyphrase Extraction using Self and Cross Attentions ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ding, Haoran; Luo, Xiao. - : Underline Science Inc., 2021 BASE Show details 14 Automatic Fact-Checking with Document-level Annotations using BERT and Multiple Instance Learning ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Park, Joonsuk; Sathe, Aalok. - : Underline Science Inc., 2021 BASE Show details 15 Towards the Early Detection of Child Predators in Chat Rooms: A BERT-based Approach ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Kumbale, Sinchana; Singh, Smriti. - : Underline Science Inc., 2021 BASE Show details 16 Semantic Categorization of Social Knowledge for Commonsense Question Answering ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Wang, Gengyu. - : Underline Science Inc., 2021 BASE Show details 17 Pre-train or Annotate? Domain Adaptation with a Constrained Budget ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bai, Fan; Ritter, Alan. - : Underline Science Inc., 2021 BASE Show details 18 Stepmothers are mean and academics are pretentious: What do pretrained language models learn about you? ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Choenni, Rochelle; Shutova, Ekaterina. - : Underline Science Inc., 2021 BASE Show details 19 CLIFF: Contrastive Learning for Improving Faithfulness and Factuality in Abstractive Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cao, Shuyang; Wang, Lu. - : Underline Science Inc., 2021 BASE Show details 20 Automatic Text Evaluation through the Lens of Wasserstein Barycenters ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Clavel, Chloe; Colombo, Pierre. - : Underline Science Inc., 2021 BASE Show details Page: 1 2 3 4 5...16

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