| Context-and sentiment-aware networks for emotion recognition in conversation G Tu, J Wen, C Liu, D Jiang, E Cambria IEEE Transactions on Artificial Intelligence 3 (5), 699-708, 2022 | 82 | 2022 |
| Dynamic interactive multiview memory network for emotion recognition in conversation J Wen, D Jiang, G Tu, C Liu, E Cambria Information Fusion 91, 123-133, 2023 | 67 | 2023 |
| Exploration meets exploitation: Multitask learning for emotion recognition based on discrete and dimensional models G Tu, J Wen, H Liu, S Chen, L Zheng, D Jiang Knowledge-Based Systems 235, 107598, 2022 | 43 | 2022 |
| A multitask learning framework for multimodal sentiment analysis D Jiang, R Wei, H Liu, J Wen, G Tu, L Zheng, E Cambria 2021 International conference on data mining workshops (ICDMW), 151-157, 2021 | 23 | 2021 |
| AutoML-Emo: Automatic knowledge selection using congruent effect for emotion identification in conversations D Jiang, R Wei, J Wen, G Tu, E Cambria IEEE Transactions on Affective Computing 14 (3), 1845-1856, 2022 | 15 | 2022 |
| Learning More from Mixed Emotions: A Label Refinement Method for Emotion Recognition in Conversations J Wen, G Tu, R Li, D Jiang, W Zhu Transactions of the Association for Computational Linguistics 11, 1485-1499, 2023 | 4 | 2023 |
| Learning More from Label Dependencies: Emotion Recognition in Conversations Models with Graph Convolutional Networks W Yu, J Wen, R Li, D Jiang | | |
