论文标题
奇怪的控制案例
The Curious Case of Control
论文作者
论文摘要
获得英语的儿童即使在近年的能力达到近年能力之后也会在主题控制句子上遇到系统错误（C. Chomsky，1969年），这可能是由于基于语义角色的启发式方法（Maratsos，1974）。鉴于大型生成语言模型的高级流利度，我们询问模型输出是否与这些启发式方法一致，并且在多大程度上不同的模型彼此一致。我们发现，模型可以通过行为分为三个单独的组，两组之间存在很大差异。最大群体中模型的输出与在主题控制下成功但在对象控制方面失败的位置启发式方法一致。鉴于对象控制是用于训练此类模型的文本数据中更频繁的数量级，因此这一结果令人惊讶。我们研究了模型在多大程度上对提示使用代理患者信息的敏感，发现提高了代理和患者关系的显着性会导致大多数模型的产出发生重大变化。基于这一观察结果，我们利用了语义原始注释的现有数据集（White等，2020）来探索控制和标记事件参与者之间具有通常与药物和患者相关的特性的标记事件参与者之间的联系。
Children acquiring English make systematic errors on subject control sentences even after they have reached near-adult competence (C. Chomsky, 1969), possibly due to heuristics based on semantic roles (Maratsos, 1974). Given the advanced fluency of large generative language models, we ask whether model outputs are consistent with these heuristics, and to what degree different models are consistent with each other. We find that models can be categorized by behavior into three separate groups, with broad differences between the groups. The outputs of models in the largest group are consistent with positional heuristics that succeed on subject control but fail on object control. This result is surprising, given that object control is orders of magnitude more frequent in the text data used to train such models. We examine to what degree the models are sensitive to prompting with agent-patient information, finding that raising the salience of agent and patient relations results in significant changes in the outputs of most models. Based on this observation, we leverage an existing dataset of semantic proto-role annotations (White, et al. 2020) to explore the connections between control and labeling event participants with properties typically associated with agents and patients.
