A new arXiv paper provides a comprehensive taxonomy of Large Language Models (LLMs), tracing their evolution from early models like BERT to contemporary systems such as GPT-5, Gemini, Claude, and Grok. The research details training datasets, computational requirements, hardware specifications, architectures, and parameters. It also addresses limitations and open challenges in LLM development, highlighting a trend where models balancing architectural complexity with data quality achieve better reasoning and alignment without excessive computational cost. AI
IMPACT Provides a structured overview of LLM development, useful for understanding the landscape and identifying future research directions.
RANK_REASON The cluster contains an academic paper detailing advancements and limitations in LLM design. [lever_c_demoted from research: ic=1 ai=1.0]
- arXiv
- BERT
- .claude
- Gemini
- generative pre-trained transformer
- GPT-5
- Grok
- Harsidak Singh Banwait
- Hugging Face
- transformer
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →