探索认知模型与语言模型融合，征集高效预训练与互动学习论文
BabyLM Turns 3: Call for papers for the 2025 BabyLM workshop
- 融合认知科学与语言建模，推动跨领域研究
- 设通用与交互双赛道，鼓励师生互动式学习
- 适合关注训练效率与可解释性研究者参与
BabyLM致力于打破认知建模与语言建模之间的界限。我们邀请提交研讨会论文，并招募研究者参与第三届BabyLM竞赛。延续往年传统，设立通用赛道的数据高效预训练挑战。今年新增交互赛道（INTERACTION），鼓励模型展现互动行为、从教师处学习，并动态调整教学内容以适应学生。同时欢迎提交与竞赛无关但相关的研究论文，涵盖训练效率、具认知合理性研究、弱模型评估等方向。
原文摘要 · Abstract (English)
BabyLM aims to dissolve the boundaries between cognitive modeling and language modeling. We call for both workshop papers and for researchers to join the 3rd BabyLM competition. As in previous years, we call for participants in the data-efficient pretraining challenge in the general track. This year, we also offer a new track: INTERACTION. This new track encourages interactive behavior, learning from a teacher, and adapting the teaching material to the student. We also call for papers outside the competition in any relevant areas. These include training efficiency, cognitively plausible research, weak model evaluation, and more.
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