📄 中文摘要
自然语言处理（NLP）不仅是人工智能的一个子领域，更是人类交流的计算体现。NLP旨在模拟语法、语义、语用和上下文之间复杂的关系，从而使机器能够解析、理解和生成更具细腻度和真实性的人类对话。研究者通过变换器模型、注意力机制和上下文嵌入等架构，探讨语言模型如何内化潜在结构、消歧义和跨领域适应。这些研究为实现更高效的语言理解和生成提供了基础，推动了NLP技术的进步。
自然语言处理连接人类意义与机器学习——我以精准和同理心构建认知模型
📄 English Summary
NLP bridges human meaning and machine learning — I engineer cognitive models with precision and empathy.
Natural Language Processing (NLP) serves as a computational embodiment of human communication, modeling the intricate relationships of syntax, semantics, pragmatics, and context. It enables systems to parse, interpret, and generate human discourse with increasing nuance and fidelity. The research focuses on transformer-based architectures, attention mechanisms, and contextual embeddings, examining how language models internalize latent structures, disambiguate polysemy, and adapt across domains. This foundational work advances the efficiency of language understanding and generation, driving progress in NLP technologies.