🧑‍🔬 Who cites Peng Fu

81 citations of their works from 79 papers of our library (of the 149,439 whose bibliographies we read) · 23 with a page here, the most cited first · ← Peng Fu

1. Multi-Modal Sarcasm Detection via Cross-Modal Graph Convolutional NetworkAnnual Meeting of the Association for Computational Linguistics (ACL)Bin Liang, Chenwei Lou, Xiang Li, et al.2022 · 172 citations
2. Towards Multi-Modal Sarcasm Detection via Hierarchical Congruity Modeling with Knowledge EnhancementConference on Empirical Methods in Natural Language Processing (EMNLP)Hui Liu, Wenya Wang, Haoliang Li2022 · 132 citations
3. Dynamic Routing Transformer Network for Multimodal Sarcasm DetectionAnnual Meeting of the Association for Computational Linguistics (ACL)Yuan Tian, Nan Xu, Ruike Zhang, et al.2023 · 66 citations
4. MMSD2.0: Towards a Reliable Multi-modal Sarcasm Detection SystemFindings of the Association for Computational LinguisticsLibo Qin, Shijue Huang, Qiguang Chen, et al.2023 · 65 citations
5. When did you become so smart, oh wise one?! Sarcasm Explanation in Multi-modal Multi-party DialoguesAnnual Meeting of the Association for Computational Linguistics (ACL)Shivani Kumar, Atharva Kulkarni, Md Shad Akhtar, et al.2022 · 51 citations
6. What Does Your Smile Mean? Jointly Detecting Multi-Modal Sarcasm and Sentiment Using Quantum ProbabilityFindings of the Association for Computational LinguisticsYaochen Liu, Yazhou Zhang, Qiuchi Li, et al.2021 · 43 citations
7. SarcasmBench: Towards Evaluating Large Language Models on Sarcasm UnderstandingarXiv:2408.11319Yazhou Zhang, Chunwang Zou, Zheng Lian, et al.2024 · 35 citations
8. A Dual-Channel Framework for Sarcasm Recognition by Detecting Sentiment ConflictFindings of the Association for Computational LinguisticsYiyi Liu, Yequan Wang, Aixin Sun, et al.2022 · 34 citations
9. Leveraging Generative Large Language Models with Visual Instruction and Demonstration Retrieval for Multimodal Sarcasm DetectionConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Binghao Tang, Boda Lin, Haolong Yan, et al.2024 · 33 citations
10. Multimodal Sarcasm Target Identification in TweetsAnnual Meeting of the Association for Computational Linguistics (ACL)Jiquan Wang, Lin Sun, Yi Liu, et al.2022 · 28 citations
11. A Survey of Multimodal Sarcasm DetectionarXiv:2410.18882Shafkat Farabi, Tharindu Ranasinghe, Diptesh Kanojia, et al.2024 · 26 citations
12. Prompt Tuning with Contradictory Intentions for Sarcasm RecognitionConference of the European Chapter of the Association for Computational Linguistics (EACL)Yiyi Liu, Ruqing Zhang, Yixing Fan, et al.2023 · 24 citations
13. Generalizable Sarcasm Detection is Just Around the Corner, of Course!Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)Hyewon Jang, Diego Frassinelli2024 · 22 citations
14. CofiPara: A Coarse-to-fine Paradigm for Multimodal Sarcasm Target Identification with Large Multimodal ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Zixin Chen, Hongzhan Lin, Ziyang Luo, et al.2024 · 20 citations
15. Inner Thinking Transformer: Leveraging Dynamic Depth Scaling to Foster Adaptive Internal ThinkingAnnual Meeting of the Association for Computational Linguistics (ACL)Yilong Chen, Junyuan Shang, Zhenyu Zhang, et al.2025 · 16 citations
16. Just Like a Human Would, Direct Access to Sarcasm Augmented with Potential Result and ReactionAnnual Meeting of the Association for Computational Linguistics (ACL)Changrong Min, Ximing Li, Liang Yang, et al.2023 · 16 citations
17. A Survey in Automatic Irony Processing: Linguistic, Cognitive, and Multi-X PerspectivesQingcheng Zeng, An-Ran Li2022 · 14 citations
18. PALI-NLP at SemEval-2022 Task 6: iSarcasmEval- Fine-tuning the Pre-trained Model for Detecting Intended SarcasmInternational Workshop on Semantic Evaluation (SemEval)Xiyang Du, Dou Hu, Jin Zhi, et al.2022 · 7 citations
19. Multi-modal Sarcasm Generation: Dataset and SolutionFindings of the Association for Computational LinguisticsWenye Zhao, Qingbao Huang, Dongsheng Xu, et al.2023 · 6 citations
20. Continuous Attentive Multimodal Prompt Tuning for Few-Shot Multimodal Sarcasm DetectionConference on Computational Natural Language Learning (CoNLL)Soumyadeep Jana, Animesh Dey, Ranbir Singh Sanasam2024 · 5 citations
21. Personalized Intended and Perceived Sarcasm Detection on TwitterProceedings of the 3rd Workshop on Computational Linguistics for the Political and Social SciencesJoan Plepi, Magdalena Buski, Lucie Flek2023 · 1 citation
22. Who You Are, What You Say: Intra- and Inter- Context Personality for Emotion Recognition in ConversationFindings of the Association for Computational LinguisticsTazeek Bin Abdur Rakib, Lay-Ki Soon, Wern Han Lim2026
23. Was that Sarcasm?: A Literature Survey on Sarcasm DetectionarXiv:2412.00425Harleen Kaur Bagga, Jasmine Bernard, Sahil Shaheen, et al.2024

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