---
title: "Who cites MMC: Advancing Multimodal — 57 citing papers"
description: "57 papers of the Elamur Research library cite «MMC: Advancing Multimodal Chart Understanding with Large-scale Instruction Tuning», found…"
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---
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# Who cites «MMC: Advancing Multimodal Chart Understanding with Large-scale Instruction Tuning»

57 papers of our library cite it (of the 141,840 whose bibliographies we read) · 7 with a page here, the most cited first · [← back to «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/)

1. **[How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites](https://md.research.elamur.ai/free/en/papers/chen-2024-far-gpt-4v-closing/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhe Chen, Weiyun Wang, Hao Tian, et al.*2024 · 529 citations*
2. [**Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling arXiv:2412.05271**Zhe Chen, Weiyun Wang, Yue Cao, et al.*2024 · 276 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-expanding-performance-boundaries-open/)
3. **[Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models](https://md.research.elamur.ai/free/en/papers/deitke-2024-molmo-pixmo-open-weights-open/) [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/)**Matt Deitke, Christopher Clark, Sangho Lee, et al.*2024 · 184 citations*
4. [**From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning arXiv:2308.12032**Ming Li, Yong Zhang, Zhitao Li, et al.*2023 · 157 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-quantity-quality-boosting-llm-performance/)
5. [**InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model arXiv:2401.16420**Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.*2024 · 92 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-internlm-xcomposer2-mastering-free/)
6. [**Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning arXiv:2402.00530**Ming Li, Yong Zhang, Shwai He, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-superfiltering-weak-strong-data-filtering/)
7. **[Assessing Y-Axis Influence: Bias in Multimodal Language Models on Chart-to-Table Translation](https://md.research.elamur.ai/free/en/papers/song-2026-assessing-y-axis-influence-bias/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Seok Hwan Song, Azher Ahmed Efat, Wallapak Tavanapong*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/liu-2024-mmc-advancing-multimodal-chart-understanding/) — MMC: Advancing Multimodal Chart Understanding with Large-scale Instruction Tuning