---
title: "Who cites Reka Core, Flash, and Edge: A — 39 citing papers"
description: "39 papers of the Elamur Research library cite «Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/ormazabal-2024-reka-core-flash-edge-series/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Reka Core, Flash, and Edge: A Series of Powerful…](https://md.research.elamur.ai/free/en/papers/ormazabal-2024-reka-core-flash-edge-series/) / cited by

# Who cites «Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models»

39 papers of our library cite it (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · [← back to «Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models»](https://md.research.elamur.ai/free/en/papers/ormazabal-2024-reka-core-flash-edge-series/)

1. **[MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI](https://md.research.elamur.ai/free/en/papers/yue-2023-mmmu-massive-multi-discipline-multimodal/) [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/)**Xiang Yue, Yuansheng Ni, Kai Zhang, et al.*2023 · 1,005 citations*
2. **[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 · 541 citations*
3. **[Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-multimodal-arxiv-dataset-improving-scientific/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lei Li, Yuqi Wang, Runxin Xu, et al.*2024 · 129 citations*
4. **[LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-lmms-eval-reality-check-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaichen Zhang, Bo Li, Peiyuan Zhang, et al.*2025 · 115 citations*
5. [**ALLaM: Large Language Models for Arabic and English arXiv:2407.15390**M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/bari-2024-allam-large-language-models-arabic/)
6. [**Reuse, Don't Retrain: A Recipe for Continued Pretraining of Language Models arXiv:2407.07263**Jupinder Parmar, Sanjev Satheesh, Mostofa Patwary, et al.*2024 · 36 citations*](https://md.research.elamur.ai/free/en/papers/parmar-2024-reuse-don-t-retrain-recipe/)
7. **[Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations](https://md.research.elamur.ai/free/en/papers/hagele-2024-scaling-laws-compute-optimal-training/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Alexander Hägele, Elie Bakouch, Atli Kosson, et al.*2024 · 31 citations*
8. [**Vibe-Eval: A hard evaluation suite for measuring progress of multimodal language models arXiv:2405.02287**Piotr Padlewski, Max Bain, Matthew Henderson, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/padlewski-2024-vibe-eval-hard-evaluation-suite/)
9. **[OmniBench: Towards The Future of Universal Omni-Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-omnibench-towards-future-universal-omni/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yizhi Li, Yinghao Ma, Ge Zhang, et al.*2024 · 17 citations*
10. **[Auto-Arena: Automating LLM Evaluations with Agent Peer Battles and Committee Discussions](https://md.research.elamur.ai/free/en/papers/zhao-2025-auto-arena-automating-llm-evaluations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruochen Zhao, Wenxuan Zhang, Yew Ken Chia, et al.*2025 · 16 citations*
11. [**Cutting Through the Noise: Boosting LLM Performance on Math Word Problems**Ujjwala Anantheswaran, Himanshu Gupta, Kevin Scaria, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/anantheswaran-2024-cutting-through-noise-boosting-llm/)
12. **[Multimodal LLMs Do Not Compose Skills Optimally across Modalities](https://md.research.elamur.ai/free/en/papers/ontalvilla-2026-multimodal-llms-do-not-compose/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Paula Ontalvilla, Aitor Ormazabal, Gorka Azkune*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/ormazabal-2024-reka-core-flash-edge-series/) — Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models
