• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 24 matches

• 2024
• 
  Meenaxi Tank, Priyank Thakkar:
  Abstractive text summarization using adversarial learning and deep neural network. Multim. Tools Appl. 83(17): 50849-50870 (2024)
• 
  Shuaiqi Liu, Jiannong Cao, Zhongfen Deng, Wenting Zhao, Ruosong Yang, Zhiyuan Wen, Philip S. Yu:
  Neural Abstractive Summarization for Long Text and Multiple Tables. IEEE Trans. Knowl. Data Eng. 36(6): 2572-2586 (2024)
• 
  Yllias Chali, Wenzhao Zhu:
  Abstractive Text Summarization Based on Neural Fusion. FLAIRS 2024
• 
  Bhavith Chandra Challagundla, Chakradhar Peddavenkatagari:
  Neural Sequence-to-Sequence Modeling with Attention by Leveraging Deep Learning Architectures for Enhanced Contextual Understanding in Abstractive Text Summarization. CoRR abs/2404.08685 (2024)
• 2023
• 
  Aniqa Dilawari, Muhammad Usman Ghani Khan, Summra Saleem, Zahoor-Ur Rehman, Fatema Sabeen Shaikh:
  Neural Attention Model for Abstractive Text Summarization Using Linguistic Feature Space. IEEE Access 11: 23557-23564 (2023)
• 
  Sandeep Kumar, Arun Solanki:
  An abstractive text summarization technique using transformer model with self-attention mechanism. Neural Comput. Appl. 35(25): 18603-18622 (2023)
• 
  Ngoc-Khuong Nguyen, Viet Ha Nguyen, Anh-Cuong Le:
  A Local Attention-based Neural Networks for Abstractive Text Summarization. APIT 2023: 152-159
• 2022
• 
  Hassan Aliakbarpour, Mohammad Taghi Manzuri, Amir Masoud Rahmani:
  Improving the readability and saliency of abstractive text summarization using combination of deep neural networks equipped with auxiliary attention mechanism. J. Supercomput. 78(2): 2528-2555 (2022)
• 2021
• 
  Ayesha Ayub Syed, Ford Lumban Gaol, Tokuro Matsuo:
  A Survey of the State-of-the-Art Models in Neural Abstractive Text Summarization. IEEE Access 9: 13248-13265 (2021)
• 
  Tian Shi, Yaser Keneshloo, Naren Ramakrishnan, Chandan K. Reddy:
  Neural Abstractive Text Summarization with Sequence-to-Sequence Models. Trans. Data Sci. 2(1): 1:1-1:37 (2021)
• 
  Min Yang, Chengming Li, Ying Shen, Qingyao Wu, Zhou Zhao, Xiaojun Chen:
  Hierarchical Human-Like Deep Neural Networks for Abstractive Text Summarization. IEEE Trans. Neural Networks Learn. Syst. 32(6): 2744-2757 (2021)
• 2020
• 
  Huan Zhao, Jie Cao, Mingquan Xu, Jian Lu:
  Variational neural decoder for abstractive text summarization. Comput. Sci. Inf. Syst. 17(2): 537-552 (2020)
• 
  Dennis Singh Moirangthem, Minho Lee:
  Abstractive summarization of long texts by representing multiple compositionalities with temporal hierarchical pointer generator network. Neural Networks 124: 1-11 (2020)
• 
  Heena Kumari, Sunita Sarkar, Vikrant Rajput, Arindam Roy:
  Comparative Analysis of Neural Models for Abstractive Text Summarization. MIND (2) 2020: 357-368
• 2019
• 
  Celia Cintas, William Ogallo, Aisha Walcott, Sekou L. Remy, Victor Akinwande, Samuel Osebe:
  Towards neural abstractive clinical trial text summarization with sequence to sequence models. ICHI 2019: 1-3
• 
  Xuewen Chen, Jinlong Li, Hai-Han Wang:
  Keyphrase Guided Beam Search for Neural Abstractive Text Summarization. IJCNN 2019: 1-9
• 
  Tian Shi, Ping Wang, Chandan K. Reddy:
  LeafNATS: An Open-Source Toolkit and Live Demo System for Neural Abstractive Text Summarization. NAACL-HLT (Demonstrations) 2019: 66-71
• 
  Soheil Esmaeilzadeh, Gao Xian Peh, Angela Xu:
  Neural Abstractive Text Summarization and Fake News Detection. CoRR abs/1904.00788 (2019)
• 
  Tian Shi, Ping Wang, Chandan K. Reddy:
  LeafNATS: An Open-Source Toolkit and Live Demo System for Neural Abstractive Text Summarization. CoRR abs/1906.01512 (2019)
• 2018
• 
  Dipanwita Debnath, Partha Pakray, Ranjita Das, Alexander F. Gelbukh:
  An Abstractive Text Summarization Using Recurrent Neural Network. CICLing (2) 2018: 364-378
• 
  Chandra Khatri, Gyanit Singh, Nish Parikh:
  Abstractive and Extractive Text Summarization using Document Context Vector and Recurrent Neural Networks. CoRR abs/1807.08000 (2018)
• 
  Tian Shi, Yaser Keneshloo, Naren Ramakrishnan, Chandan K. Reddy:
  Neural Abstractive Text Summarization with Sequence-to-Sequence Models. CoRR abs/1812.02303 (2018)
• 2016
• 
  Gaetano Rossiello:
  Neural Abstractive Text Summarization. DC@AI*IA 2016: 70-75
• 
  Gaetano Rossiello, Pierpaolo Basile, Giovanni Semeraro, Marco Di Ciano, Gaetano Grasso:
  Improving Neural Abstractive Text Summarization with Prior Knowledge (Position Paper). URANIA@AI*IA 2016: 13-18