Neural Sequence-to-Sequence Modeling with Attention by Leveraging Deep Learning Architectures for Enhanced Contextual Understanding in Abstractive Text Summarization

8 April 2024

Papers citing "Neural Sequence-to-Sequence Modeling with Attention by Leveraging Deep Learning Architectures for Enhanced Contextual Understanding in Abstractive Text Summarization"

10 / 10 papers shown

Title
A Fine-Tuning Approach for T5 Using Knowledge Graphs to Address Complex Tasks Xiaoxuan Liao Binrong Zhu Jacky He Guiran Liu Hongye Zheng Jia Gao 81 7 0 23 Feb 2025
Moving Down the Long Tail of Word Sense Disambiguation with Gloss-Informed Biencoders Terra Blevins Luke Zettlemoyer 66 166 0 06 May 2020
SemEval-2017 Task 3: Community Question Answering Preslav Nakov Doris Hoogeveen Lluís Màrquez i Villodre Alessandro Moschitti Hamdy Mubarak Timothy Baldwin Karin Verspoor 56 228 0 02 Dec 2019
Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings Gregor Wiedemann Steffen Remus Avi Chawla Chris Biemann 77 176 0 23 Sep 2019
GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge Luyao Huang Chi Sun Xipeng Qiu Xuanjing Huang 54 243 0 20 Aug 2019
EmbraceNet: A robust deep learning architecture for multimodal classification Jun-Ho Choi Jong-Seok Lee 51 125 0 19 Apr 2019
NCRF++: An Open-source Neural Sequence Labeling Toolkit Jie Yang Yue Zhang 84 190 0 14 Jun 2018
Attending to Characters in Neural Sequence Labeling Models Marek Rei Gamal K. O. Crichton S. Pyysalo 91 187 0 14 Nov 2016
sense2vec - A Fast and Accurate Method for Word Sense Disambiguation In Neural Word Embeddings Andrew Trask Phillip Michalak John Chih Liu 55 173 0 19 Nov 2015
Sequence to Sequence Learning with Neural Networks Ilya Sutskever Oriol Vinyals Quoc V. Le AIMat 448 20,606 0 10 Sep 2014