多模态情感分析论文整理(2021-2023)

MABSA下游任务论文整理

  • 一.MASC任务
    • (一)基于注意力模型的相关论文
    • (二) 基于图卷积网络(GCN)的相关论文
  • 二.ASPE任务
    • (一)PIPELINE-BASED ASPE METHOD
    • (二)JOINT-BASED ASPE METHOD
    • (三)UNIFIED-BASED ASPE METHOD
    • (四) TEXT GENERATION-BASED ASPE METHOD

一.MASC任务

(一)基于注意力模型的相关论文

  1. ‘‘Show, attend and tell: Neural image caption
    generation with visual attention,’’ Comput. Sci. 2015
  2. ‘‘Multi-interactive memory network
    for aspect based multimodal sentiment analysis,’’ . AAAI, 2019,
  3. ‘‘Entity-sensitive attention and fusion network for entity-level multimodal sentiment classification,’’ IEEE/ACM Trans. Audio, Speech, Language Process., 2020
  4. ‘‘ABAFN: Aspect-based sentiment analysis model for multimodal,’’ Comput. Eng. Appl., 2022
  5. ‘‘Targeted aspect-based multimodal sentiment analysis: An
    attention capsule extraction and multi-head fusion network,’’ IEEE
    Access, 2021
  6. ‘Hierarchical interactive multimodal transformer for aspect-based multimodal sentiment analysis,’’ IEEE Trans. Affect. Comput., 2022
  7. ‘‘Research on multimodal fine-grained sentiment analysis method based on cross-modal transformer,’’ Comput. Digit. Eng2022
  8. ‘‘Targeted multimodal sentiment classification based on coarse-to-fine grained image-target matching,’’ IJCAI 2022
  9. Image-text aspect emotion recognition based on joint aspect attention interaction,’’ Beijing Univ. Aeronaut. Astronaut., 2022

(二) 基于图卷积网络(GCN)的相关论文

  1. ‘‘Aspect-level multimodal sentiment analysis based on
    interaction graph neural network,’’ Appl. Res. Comput., 2023
    2.‘Multiview interaction learning network for multimodal aspect-level sentiment analysis,’’ Comput. Eng. Appl., 2023
  2. ‘‘Fusion with GCN and SE-ResNeXt network for aspect based multimodal sentiment analysis,’’ ITNEC 2023,
  3. Aspect-level multimodal co-attention graph convolutional sentiment analysis model,’ Image Graph., 2023.

二.ASPE任务

(一)PIPELINE-BASED ASPE METHOD

  1. ‘Joint multi-modal aspect-sentiment analysis with auxiliary cross-modal
    relation detection,’’ EMNLP 2021

(二)JOINT-BASED ASPE METHOD

  1. End-to-end aspectbased sentiment analysis model for BERT and LSI,’’ Comput. Eng. Appl.,2023
  2. A unified framework for multimodal aspect-term extraction and aspect-level sentiment classification,J. Comput. Res. Device, 2023

(三)UNIFIED-BASED ASPE METHOD

  1. Cross-modal multitask transformer for end-to-end multimodal aspect-based sentiment analysis,’’ Inf. Process. Manag.,2022
  2. Dual-encoder transformers with cross-modal alignment for multimodal aspect-based sentiment analysis, AACL IJCNLP, 2022

(四) TEXT GENERATION-BASED ASPE METHOD

  1. ‘‘Vision-language pre-training for multimodal aspect-based sentiment analysis,’’ ACL 2022
    2.AoM: Detecting aspect-oriented information for multimodal aspect-based sentiment analysis,’’ ACL, 2023
  2. Few-shot joint multimodal aspect-sentiment analysis based on generative multimodal prompt, ACL 2023,

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