New conference paper! (Adolfi et al., CogSci, 2025)

A conference paper from Federico and Yue was accepted at CogSci 2025! [link]

Adolfi F, Sun Y, Poeppel D (2025). Content-agnostic online segmentation as a core operation. Proceedings of the Annual Meeting of the Cognitive Science Society

We approach the problem of explaining segmentation — the human capacity to partition input streams into representations of appropriate form and content for efficient downstream processing — by exploring a theoretically minimalistic and computationally plausible account of phoneme-to-word chunking. Through computational models, mathematical proofs, algorithm design, and observer model simulations in two languages, we suggest that online segmentation can be guided by content-agnostic properties of internal memory structures (i.e., lexicality and length type frequency). Our theoretical and empirical findings point to a formal link between such properties with practical performance benefits. Together, these contributions make progress on a fully explicit computational- and algorithmic-level account with plausible implementational-level primitives.