分析了上万篇论文，发现对话术语拼写混乱且长期未统一。
"Dialogue" vs "Dialog" in NLP and AI research: Statistics from a Confused Discourse
- 统计顶级会议论文，72%用dialogue，24%用dialog，5%混用
- 近20年无明显拼写趋势变化，作者国籍影响微弱
- 拼写受上下文影响有限，可能源于学术传统差异
在计算研究中，'dialogue'和'dialog'两种拼法并存，成为日益重要的术语。我们分析了数千篇论文，探究这一'拼写混乱'现象。在标题或摘要中使用‘dialog(ue)’的顶会论文中，72%采用‘dialogue’，24%采用‘dialog’，5%在同一文献中混用。这种分裂现象在计算机领域比其他学科更为普遍。我们考察了近20年NLP/AI研究中的趋势，未发现明确的演变迹象。作者国籍与拼写选择仅有弱相关，无法解释混用现象。许多高产作者同时发表两种拼写的论文。通过句法解析和语言模型嵌入等方法，我们发现语境对拼写影响有限。综合以上结果，讨论可能导致拼写分歧的多种理论。
原文摘要 · Abstract (English)
Within computing research, there are two spellings for an increasingly important term - dialogue and dialog. We analyze thousands of research papers to understand this "dialog(ue) debacle". Among publications in top venues that use "dialog(ue)" in the title or abstract, 72% use "dialogue", 24% use "dialog", and 5% use both in the same title and abstract. This split distribution is more common in Computing than any other academic discipline. We investigate trends over ~20 years of NLP/AI research, not finding clear evidence of a shift over time. Author nationality is weakly correlated with spelling choice, but far from explains the mixed use. Many prolific authors publish papers with both spellings. We use several methods (such as syntactic parses and LM embeddings) to study how dialog(ue) context influences spelling, finding limited influence. Combining these results together, we discuss different theories that might explain the dialog(ue) divergence.
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