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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...13 Hits 1 – 20 of 244 1 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 2 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 3 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 4 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 5 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; S. Yu, Philip; Wan, Yao; Xia, Congying; Zhang, Jianguo. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.13/ Abstract: To capture the semantic graph structure from raw text, most existing summarization approaches are built on GNNs with a pre-trained model. However, these methods suffer from cumbersome procedures and inefficient computations for long-text documents. To mitigate these issues, this paper proposes HETFORMER, a Transformer-based pre-trained model with multi-granularity sparse attentions for long-text extractive summarization. Specifically, we model different types of semantic nodes in raw text as a potential heterogeneous graph and directly learn heterogeneous relationships (edges) among nodes by Transformer. Extensive experiments on both single- and multi-document summarization tasks show that HETFORMER achieves state-of-the-art performance in Rouge F1 while using less memory and fewer parameters. ... Keyword: Computational Linguistics; Language Models; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Text Summarization URL: https://underline.io/lecture/37574-hetformer-heterogeneous-transformer-with-sparse-attention-for-long-text-extractive-summarization https://dx.doi.org/10.48448/za5a-2696 BASE Hide details 6 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 7 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 8 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 9 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 10 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 11 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 12 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 13 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 14 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 15 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 16 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 17 Combining sentence and table evidence to predict veracity of factual claims using TaPaS and RoBERTa ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Funkquist, Martin. - : Underline Science Inc., 2021 BASE Show details 18 Meta Distant Transfer Learning for Pre-trained Language Models ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Wang, Chengyu. - : Underline Science Inc., 2021 BASE Show details 19 How to Train BERT with an Academic Budget ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Berchansky, Moshe; Izsak, Peter. - : Underline Science Inc., 2021 BASE Show details 20 Temporal Adaptation of BERT and Performance on Downstream Document Classification: Insights from Social Media ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021. - : Underline Science Inc., 2021 BASE Show details Page: 1 2 3 4 5...13

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