The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Comprehensive Examination of Instruction-Based Language Models: A Comparative Analysis of Mistral-7B and Llama-2-7B
Abstract
In natural language processing and computer vision, both of which are developing rapidly, analytical methods are very important to improve modeling This study uses ROUGE, BLEU, and CIDEr as key performance indicators to assess how Mistral-7b and Llama-2-7b are better model perform. The preliminary results show that the LAMA-2-7b is the best in all dimensions. Despite these results, the new Mistral-7b, which is supposedly more capable, may still be in the data collection stage, needing larger datasets to shine This article learns more about their capabilities and how important they are to give testing examples continue to illuminate.
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Mistral has an 8k context window.
“Notably, Mistral has an 8k context window, which allows for a more complete understanding of context compared to the 4k context window of Llama 2 [28].”
From Evaluating Large Language Models for Structured Science Summarization in the Open Research Knowledge Graph (2024) · cites this paper as [28]
Llama 2 has a 4k context window.
“Notably, Mistral has an 8k context window, which allows for a more complete understanding of context compared to the 4k context window of Llama 2 [28].”
From Evaluating Large Language Models for Structured Science Summarization in the Open Research Knowledge Graph (2024) · cites this paper as [28]
Citations
Cites
LoRA: Low-Rank Adaptation of Large Language Models
Hu, E. J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., & Chen, W. (2021) · arXiv · doi:10.48550/arxiv.2106.09685 · Cited by 13,453
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3442188.3445922 · Cited by 6,988 · cited 2×
“These features of focused enhancements, in combination with its attention mechanisms makes Mistral 7B , an efficient language model in both performance also well as resource structured in contrast to the traditional transformer architecture of LLaMa[12]. make Mistral 7B a high-performance and resource-efficient langua…”
BackgroundA Survey of Large Language Models
Zhao, W. X., Zhou, K., Li, J., Tang, T., Dong, Z., Hou, Y., Zhang, B., Min, Y., Zhang, J., Liu, P., et al. (2026) · Frontiers of Computer Science · doi:10.1007/s11704-026-60308-3 · Cited by 2,093 · cited 2×
“[10].”
BackgroundA Survey of Large Language Models
Zhao, W. X., Zhou, K., Li, J., Tang, T., Wang, X., Hou, Y., Min, Y., Zhang, B., Zhang, J., Dong, Z., et al. (2023) · arXiv · doi:10.48550/arxiv.2303.18223 · Cited by 2,090
Flagged first, then by citations
Research works printed but not linked: 4
- Aman’s AI Journal • Models • LLaMA
- A, 2023, LLama 2 Training, Llama, 2
- 10.2307/j.ctv1tjrvk1.47 · DOI
- Hu, 2022, LoRA: Low-Rank Adaptation of Large Language Models - Microsoft Research
Cited by
Sorted by citations
Nechakhin, V., D’Souza, J., & Eger, S. (2024) · Information · doi:10.3390/info15060328 · Cited by 17
Metadata
- Authors
- Thakkar, H., & Manimaran, A.
- Venue
- 2023 International Conference on Emerging Research in Computational Science (ICERCS)
- Publisher
- IEEE
- Published
- 2023-12-07
- Pages
- 1-6
- Cited by
- 42
- References
- 4
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