---
title: "Who cites Investigating the Catastrophic — 43 citing papers"
description: "43 papers of the Elamur Research library cite «Investigating the Catastrophic Forgetting in Multimodal Large Language Models», found in their…"
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---
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# 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»](https://md.research.elamur.ai/free/en/papers/zhai-2023-investigating-catastrophic-forgetting-multimodal-large/)

1. **[Survey of Hallucination in Natural Language Generation](https://md.research.elamur.ai/free/en/papers/ji-2022-survey-hallucination-natural-language-generation/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Ziwei 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 Models](https://md.research.elamur.ai/free/en/papers/guan-2023-hallusionbench-advanced-diagnostic-suite-entangled/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Tianrui Guan, Fuxiao Liu, Xiyang Wu, et al.*2023 · 335 citations*
3. **[Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/tong-2024-cambrian-1-fully-open-vision/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shengbang Tong, Ellis Brown, Penghao Wu, et al.*2024 · 208 citations*
4. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity arXiv:2310.07521**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
5. **[MMC: Advancing Multimodal Chart Understanding with Large-scale Instruction Tuning](https://md.research.elamur.ai/free/en/papers/liu-2024-mmc-advancing-multimodal-chart-understanding/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Fuxiao Liu, Xiaoyang Wang, Wenlin Yao, et al.*2024 · 86 citations*
6. **[Continuous Attentive Multimodal Prompt Tuning for Few-Shot Multimodal Sarcasm Detection](https://md.research.elamur.ai/free/en/papers/jana-2024-continuous-attentive-multimodal-prompt-tuning/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Soumyadeep Jana, Animesh Dey, Ranbir Singh Sanasam*2024 · 5 citations*
7. **[PlaM: Training-Free Plateau-Guided Model Merging for Better Visual Grounding in MLLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-plam-training-free-plateau-guided/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zijing Wang, YongKang Liu, Mingyang Wang, et al.*2026 · 1 citation*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/zhai-2023-investigating-catastrophic-forgetting-multimodal-large/) — Investigating the Catastrophic Forgetting in Multimodal Large Language Models