1105mp4 May 2026

3. Text Categorization by Learning Predominant Sense of Words (2019) Machine Learning / NLP

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

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 1105mp4

This paper uses a Transformer-based model to categorize documents more accurately by figuring out the specific meaning of a word based on the domain it's used in (e.g., "bank" in finance vs. "bank" in geography). Source: ACL Anthology P19-1105 1105mp4