State of the art: a review of sentiment analysis based on sequential transfer learning

JYL Chan, KT Bea, SMH Leow, SW Phoong… - Artificial Intelligence …, 2023 - Springer
Recently, sequential transfer learning emerged as a modern technique for applying the
“pretrain then fine-tune” paradigm to leverage existing knowledge to improve the …

Progress, achievements, and challenges in multimodal sentiment analysis using deep learning: A survey

A Pandey, DK Vishwakarma - Applied Soft Computing, 2024 - Elsevier
Sentiment analysis is a computational technique that analyses the subjective information
conveyed within a given expression. This encompasses appraisals, opinions, attitudes or …

Hybrid contrastive learning of tri-modal representation for multimodal sentiment analysis

S Mai, Y Zeng, S Zheng, H Hu - IEEE Transactions on Affective …, 2022 - ieeexplore.ieee.org
The wide application of smart devices enables the availability of multimodal data, which can
be utilized in many tasks. In the field of multimodal sentiment analysis, most previous works …

Cross-modal prototype driven network for radiology report generation

J Wang, A Bhalerao, Y He - European Conference on Computer Vision, 2022 - Springer
Radiology report generation (RRG) aims to describe automatically a radiology image with
human-like language and could potentially support the work of radiologists, reducing the …

Multimodal information bottleneck: Learning minimal sufficient unimodal and multimodal representations

S Mai, Y Zeng, H Hu - IEEE Transactions on Multimedia, 2022 - ieeexplore.ieee.org
Learning effective joint embedding for cross-modal data has always been a focus in the field
of multimodal machine learning. We argue that during multimodal fusion, the generated …

Disentanglement translation network for multimodal sentiment analysis

Y Zeng, W Yan, S Mai, H Hu - Information Fusion, 2024 - Elsevier
Obtaining an effective joint representation has always been the goal for multimodal tasks.
However, distributional gap inevitably exists due to the heterogeneous nature of different …

SKEAFN: sentiment knowledge enhanced attention fusion network for multimodal sentiment analysis

C Zhu, M Chen, S Zhang, C Sun, H Liang, Y Liu… - Information …, 2023 - Elsevier
Multimodal sentiment analysis is an active research field that aims to recognize the user's
sentiment information from multimodal data. The primary challenge in this field is to develop …

BiSyn-GAT+: Bi-syntax aware graph attention network for aspect-based sentiment analysis

S Liang, W Wei, XL Mao, F Wang, Z He - arxiv preprint arxiv:2204.03117, 2022 - arxiv.org
Aspect-based sentiment analysis (ABSA) is a fine-grained sentiment analysis task that aims
to align aspects and corresponding sentiments for aspect-specific sentiment polarity …

Contrastive learning based modality-invariant feature acquisition for robust multimodal emotion recognition with missing modalities

R Liu, H Zuo, Z Lian, BW Schuller… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Multimodal emotion recognition (MER) aims to understand the way that humans express
their emotions by exploring complementary information across modalities. However, it is …

A comprehensive survey on deep learning-based approaches for multimodal sentiment analysis

A Ghorbanali, MK Sohrabi - Artificial Intelligence Review, 2023 - Springer
Sentiment analysis is an important natural language processing issue that has many
applications in various fields. The increasing popularity of social networks and growth and …