Taxonomy formalizes curriculum learning strategy selection for NLP
A new taxonomy for curriculum learning in NLP addresses a decade-long gap in the field: practitioners lack principled guidance on selecting difficulty functions and training schedules for specific tasks. This work separates difficulty evaluation from scheduling mechanics, formalizing how instances are ranked by hardness and how models should consume them during training. The framework distinguishes between attribution sources and task dependencies, revealing that 'difficulty' itself encodes different assumptions about learning. For practitioners building production NLP systems, this taxonomy offers a systematic way to compare and select curriculum strategies rather than relying on ad-hoc choices, potentially improving sample efficiency and convergence across diverse applications.
Modelwire context
ExplainerThe paper's key contribution isn't just cataloging curriculum strategies that already exist, but separating the question of 'what makes an instance hard?' from 'in what order should the model see hard instances?' This distinction reveals that difficulty itself is task-dependent and assumption-laden, not a universal property.
This taxonomy work sits upstream of the supervision restructuring problem tackled in DAIS (the intermediate QA supervision paper from today). DAIS shows that intermediate steps need dependency-aware conditioning, but it doesn't systematize how to rank which intermediate steps are 'easier' to learn first. The curriculum taxonomy provides the formal language to ask that question. Similarly, the speech tokenization work (PINT, also today) implicitly assumes some instances are harder to tokenize cleanly than others, but lacks a principled framework for ordering training on noisy versus clean utterances. This paper gives practitioners the vocabulary to make those choices explicit rather than implicit.
If major NLP frameworks (Hugging Face, PyTorch Lightning) ship curriculum learning utilities that explicitly reference this taxonomy's distinction between difficulty attribution and scheduling within the next 12 months, adoption is real. If papers continue proposing curriculum strategies without citing this taxonomy as their organizing framework, it remains academic scaffolding rather than a working standard.
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