再次失去我们的尾巴：(非)自然选择与多语言大语言模型
Losing our Tail, Again: (Un)Natural Selection & Multilingual LLMs
AI总结：
本文探讨多语言大语言模型中翻译技术导致语言多样性丧失的问题，指出模型崩溃可能使语言形式、语法特征和文化内涵消失，呼吁保护多语言多样性。
摘要：
多语言大语言模型极大地改变了技术对语言的影响。尽管先前的技术能辅助人类，但现在写作任务逐渐被这些技术接管，使模型更直接地改变语言。虽然它们提供快速信息访问和流畅输出，但其表面的复杂性下隐藏着微妙的威胁：语言多样性的逐渐衰退。本文探讨模型崩溃（特别是翻译技术）如何导致语言形式、语法特征和文化细微差别丧失。模型崩溃指的是自我消耗训练循环的后果，自动生成的数据重新进入训练数据，导致数据分布逐渐扭曲和低概率语言现象的低估。基于计算机视觉、自然语言处理和机器翻译的最新研究，本文认为我们的语言分布许多尾巴可能正在消失，随之消失的是它们所承载的叙述和身份。本文呼吁抵制语言扁平化，并重新想象自然语言处理作为鼓励、重视和保护表达多语言多样性和创造力的领域。
英文摘要：
Multilingual Large Language Models considerably changed how technologies influence language. While previous technologies could mediate or assist humans, there is now a tendency to offload the task of writing itself to these technologies, enabling models to change our languages more directly. While they provide us quick access to information and impressively fluent output, beneath their (apparent) sophistication lies a subtle, insidious threat: the gradual decline and loss of linguistic diversity. In this position paper, I explore how model collapse, with a particular focus on translation technology, can lead to the loss of linguistic forms, grammatical features, and cultural nuance. Model collapse refers to the consequences of self-consuming training loops, where automatically generated data (re-)enters the training data, leading to a gradual distortion of the data distribution and the underrepresentation of low-probability linguistic phenomena. Drawing on recent work in Computer Vision, Natural Language Processing and Machine Translation, I argue that the many tails of our linguistic distributions might be vanishing, and with them, the narratives and identities they carry. This paper is a call to resist linguistic flattening and to reimagine Natural Language Processing as a field that encourages, values and protects expressive multilingual diversity and creativity.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
