🔗 Who cites «Investigating the Catastrophic Forgetting in Multimodal Large Language Models»

43 papers of our library cite it (of the 149,439 whose bibliographies we read) · 7 with a page here, the most cited first · ← back to «Investigating the Catastrophic Forgetting in Multimodal Large Language Models»

1. Survey of Hallucination in Natural Language GenerationACM Computing SurveysZiwei Ji, Nayeon Lee, Rita Frieske, et al.2022 · 5,974 citations
2. HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionTianrui Guan, Fuxiao Liu, Xiyang Wu, et al.2023 · 335 citations
3. Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMsConference on Neural Information Processing Systems (NeurIPS)Shengbang Tong, Ellis Brown, Penghao Wu, et al.2024 · 208 citations
4. Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-SpecificityarXiv:2310.07521Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.2023 · 171 citations
5. MMC: Advancing Multimodal Chart Understanding with Large-scale Instruction TuningConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Fuxiao Liu, Xiaoyang Wang, Wenlin Yao, et al.2024 · 86 citations
6. 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
7. PlaM: Training-Free Plateau-Guided Model Merging for Better Visual Grounding in MLLMsFindings of the Association for Computational LinguisticsZijing Wang, YongKang Liu, Mingyang Wang, et al.2026 · 1 citation

36 more papers of our library cite it; they have no page here yet.

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