While efforts have been made to explain computer vision models, these approaches often fall short of providing direct and human-understandable explanations.

Program translation isanimportant tool tomigrate legacycode inone language into an ecosystem built in a different language. In this work, we are the first to employ deep neural networks toward tackling this problem.

Neural Information Processing Systems http://nips.cc/

Neural Information Processing Systems http://nips.cc/

V anilla NA T model assumes that the target tokens are independent of each other given the source sentence. This assumption enables the parallel generation of all tokens.

Program translation is an important tool to migrate legacy code in one language into an ecosystem built in a different language. In this work, we are the first to employ deep neural networks toward tackling this problem.

This makes parsing intractable and requires image grammars to be severely restricted in practice, for example by allowing only rectangular regions.

Statistical analysis of corpora provides an approach to quantitatively investigate natural languages. This approach has revealed that several power laws consistently emerge across different corpora and languages, suggesting universal mechanisms underlying languages. Particularly, the power-law decay of correlation has been interpreted as evidence for underlying hierarchical structures in syntax, semantics, and discourse. This perspective has also been extended to child speeches and animal signals. However, the argument supporting this interpretation has not been empirically tested in natural languages. To address this problem, the present study examines the validity of the argument for syntactic structures. Specifically, we test whether the statistical properties of parse trees align with the assumptions in the argument. Using English and Japanese corpora, we analyze the mutual information, deviations from probabilistic context-free grammars (PCFGs), and other properties in natural language parse trees, as well as in the PCFG that approximates these parse trees. Our results indicate that the assumptions do not hold for syntactic structures and that it is difficult to apply the proposed argument to child speeches and animal signals, highlighting the need to reconsider the relationship between the power law and hierarchical structures.