Research Not III

Assessing Novelty and Prior Art in Machine Learning Papers

Novelty claims in machine learning research should be evaluated in relation to both foundational work and recent developments. Incremental improvements may offer value, but they must be clearly distinguished from genuinely new methodological contributions.

Structured literature review helps identify overlap with prior approaches, missing citations, and uncredited reuse of ideas. Clear positioning within the existing research landscape is a key indicator of scholarly integrity.

Reviewer note: Novelty should be demonstrated, not implied.