1105mp4 ❲2K❳

This paper introduces "Abstract Syntax Networks," a model designed to convert natural language descriptions into executable code (like Python or SQL) by predicting the structure of the code directly. Source: ACL Anthology P17-1105

2. Sentences with Gapping: Parsing and Reconstructing Elided Material (2018) Computational Linguistics 1105mp4

3. Text Categorization by Learning Predominant Sense of Words (2019) Machine Learning / NLP This paper introduces "Abstract Syntax Networks," a model

It focuses on how computers can understand "gapped" sentences—where words are omitted but understood (e.g., "Paul likes coffee and Mary tea"). The authors propose methods to help AI fill in these missing pieces. Source: ACL Anthology N18-1105 Text Categorization by Learning Predominant Sense of Words

The code often refers to specific academic papers in the ACL Anthology (a digital archive of conference papers on Natural Language Processing). Depending on which conference year you are looking for, here are three high-quality "1105" papers you can explore: 1. Abstract Syntax Networks for Code Generation (2017) Topic: Artificial Intelligence / Programming