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自然语言处理
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== 挑战与发展趋势 == 尽管以大语言模型为代表的技术取得了突破性进展,自然语言处理仍面临诸多挑战:模型可能生成看似合理实则错误的内容(幻觉问题)、对低资源语言支持不足、推理与常识能力有限,以及训练与部署的高昂成本。此外,模型的偏见、隐私与可解释性问题也引发广泛关注(参见 [[AI 伦理与安全]])。未来的发展趋势包括多模态融合(语言与视觉、语音结合)、增强模型的推理与规划能力、知识与大模型的结合,以及更高效的训练与推理方法。
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