Road of Large Language Model: Source, Challenge, and Future Perspectives
Language model (LM), a foundational algorithm in the development of capable artificial intelligence, has been widely explored, achieving remarkable attainment. As research advances, large language models (LLMs) have emerged by pretraining transformer-based models on large-scale corpora. These models...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Association for the Advancement of Science (AAAS)
2025-01-01
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| Series: | Research |
| Online Access: | https://spj.science.org/doi/10.34133/research.0655 |
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| Summary: | Language model (LM), a foundational algorithm in the development of capable artificial intelligence, has been widely explored, achieving remarkable attainment. As research advances, large language models (LLMs) have emerged by pretraining transformer-based models on large-scale corpora. These models showed great zero-shot and few-shot learning capabilities across a variety of tasks, attracting widespread attention from both academia and industry. Despite impressive performance, LLMs still tackle challenges in addressing complex real-world scenarios. Recently, the advent of DeepSeek has reignited intense interest among researchers. In this paper, we provide a concise development history of LLM and discuss current challenges and future perspective. In practice, we focus on 4 crucial aspects of LLMs, including emergent abilities, human alignment, retrieval augmented generation, and applications in specific domains. |
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| ISSN: | 2639-5274 |