arXiv:2607. 08063v1 Announce Type: cross Abstract: Unsupervised constituency parsing aims to accurately induce latent tree structures from raw text alone.
By Ryosuke Yamaki, Daichi Mochihashi, Nobutaka Shimada, Tadahiro Taniguchi
arXiv:2602. 06065v3 Announce Type: replace-cross Abstract: Understanding how the structure of language can be learned from sentences alone is a central question in both cognitive science and machine learning.
By Jack T. Parley, Francesco Cagnetta, Matthieu Wyart
arXiv:2606. 25987v1 Announce Type: cross Abstract: Large language models (LLMs) attain remarkable surface fluency on code, yet they neither formally guarantee the syntactic validity of their output nor leverage the hierarchical structure defining the target language.
By Alexandre Bouayad
arXiv:2604. 26157v4 Announce Type: replace-cross Abstract: Structural generalization in semantic parsing requires systems to apply learned compositional rules to novel structural combinations.
By Zichao Wei
arXiv:2510. 19698v3 Announce Type: replace Abstract: Large Language Models (LLMs) can propose rules in natural language, sidestepping the need for a predefined predicate space in traditional rule learning.
By Yang Yang, Hua XU, Zhangyi Hu, Yutao Yue
arXiv:2608. 10137v1 Announce Type: cross Abstract: Grammar Constrained Decoding (GCD) forces Language Models (LMs) to produce syntactically valid outputs by masking out non-conforming tokens at each step.
By I\c{s}{\i}l \"Ozg\"u, Yaoxuan Wu, Guy Van den Broeck, Miryung Kim