ACL wraps up today. Here’s my rundown of what was most exciting at this year’s conference.
Let me start off by describing my bias: my Ph.D. research was in conversational discourse analysis, focusing on social behaviors in language. I also wrote LightSIDE, the open source tool for feature extraction, machine learning model building, and in-depth error analysis for text data. Since I left Carnegie Mellon, I’ve been focusing on automated writing evaluation, with applications to both essay grading and generation of formative feedback directly to students.
Because of this background, I spent very little time paying attention to machine translation talks. I don’t have the mathematics background to really contribute to discussions of parsing or machine learning optimization papers. I spent most sessions in the talks on social behaviors, dialogue, and some of the more creative fields, like summarization and generation. I also really like off-kilter applications of NLP, and growing fields like digital humanities.
My criteria was that the paper was full of innovative ideas and applicable to real world problems; I care less about accuracy numbers and pushing the diminishing returns on well-known corpora and tasks. With that being said, here’s my top 10 papers from this year’s conference.[……]