Text matching in insurance question-answering community based on an integrated BiLSTM-TextCNN model fusing multi-feature
Z Li, X Yang, L Zhou, H Jia, W Li - Entropy, 2023 - mdpi.com
Along with the explosion of ChatGPT, the artificial intelligence question-answering system
has been pushed to a climax. Intelligent question-answering enables computers to simulate …
has been pushed to a climax. Intelligent question-answering enables computers to simulate …
Heterogeneous community question answering via social-aware multi-modal co-attention convolutional matching
Nowadays, community-based question answering (CQA) systems are popular and have
accumulated a large number of questions and answers provided by users. How to …
accumulated a large number of questions and answers provided by users. How to …
Reranking Passages with Coarse-to-Fine Neural Retriever using List-Context Information
H Zhu - arXiv preprint arXiv:2308.12022, 2023 - arxiv.org
Passage reranking is a crucial task in many applications, particularly when dealing with
large-scale documents. Traditional neural architectures are limited in retrieving the best …
large-scale documents. Traditional neural architectures are limited in retrieving the best …
Spatiotemporal convolutional LSTM with attention mechanism for monthly rainfall prediction
Climate has always become part of an essential role in human life on earth. Climate change
is a scorching topic because of various prediction efforts to predict the future of the earth's …
is a scorching topic because of various prediction efforts to predict the future of the earth's …
Arc loss: Softmax with additive angular margin for answer retrieval
R Suzuki, S Fujita, T Sakai - … Societies Conference, AIRS 2019, Hong Kong …, 2020 - Springer
Answer retrieval is a crucial step in question answering. To determine the best Q–A pair in a
candidate pool, traditional approaches adopt triplet loss (ie, pairwise ranking loss) for a …
candidate pool, traditional approaches adopt triplet loss (ie, pairwise ranking loss) for a …
A Comprehensive Review on Image Captioning Using Deep Learning
RK Kaushik, SK Sharma, L Kumar - International Conference on …, 2022 - Springer
Our brain is capable of annotating or classifying any image that emerges in front of us. What
about computers, though? How can a computer process an image and identify it with a …
about computers, though? How can a computer process an image and identify it with a …
A neural architecture for multi-label text classification
We propose a novel supervised approach for multi-label text classification, which is based
on a neural network architecture consisting of a single encoder and multiple classifier …
on a neural network architecture consisting of a single encoder and multiple classifier …
Encoder-Decoder Network with Cross-Match Mechanism for Answer Selection
Z Xie, X Yuan, J Wang, S Ju - … : 18th China National Conference, CCL 2019 …, 2019 - Springer
Answer selection (AS) is an important subtask of question answering (QA) that aims to
choose the most suitable answer from a list of candidate answers. Existing AS models …
choose the most suitable answer from a list of candidate answers. Existing AS models …
Check for Encoder-Decoder Network with Cross-Match Mechanism for Answer Selection Zhengwen Xie, Xiao Yuan, Jiawei Wang, and Shenggen Ju () College of …
Z Xie - … Linguistics: 18th China National Conference, CCL …, 2019 - books.google.com
Answer selection (AS) is an important subtask of question answering (QA) that aims to
choose the most suitable answer from a list of candidate answers. Existing AS models …
choose the most suitable answer from a list of candidate answers. Existing AS models …
Finding the Answers with Definition Models
J Parry - arXiv preprint arXiv:1809.00224, 2018 - arxiv.org
Inspired by a previous attempt to answer crossword questions using neural networks (Hill,
Cho, Korhonen, & Bengio, 2015), this dissertation implements extensions to improve the …
Cho, Korhonen, & Bengio, 2015), this dissertation implements extensions to improve the …