Computer Science
Using Computational Linguistics to Investigate Multiword Expressions at the Brain Level
This is the second of two sessions in which each CLIP member will take three minutes to update us on one thing they have been or will be working on.
Julia Kreutzer (Department of Computational Linguistics, Heidelberg U)
Improving Neural Machine Translation with Human Feedback
Xiaozhong Liu (School of Informatics, Computing, and Engineering; Indiana University, Bloomington)
Natural Language Processing and Text Mining with User Behavior Data
Cache Transition Systems for Semantic Parsing
Abstract: We describe a transition system that generalizes standard transition-based dependency parsing techniques to generate a graph rather than a tree. Our system includes a cache with fixed size m, and we characterize the relationship between the parameter m and the class of graphs that can be produced through the graph-theoretic concept of tree decomposition. We train a sequence-to-sequence neural model based on this system to parse text into Abstract Meaning Representation (AMR).
Title: A family of neural models for voice query understanding on an entertainment platform
CLIP Computing Infrastructure News
Title: Event Semantics in Text Constructions, Vision, and Human-Robot Dialogue
Pages
