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UMIACS

Learning to summarize medical evidence

 

Promoting Pro-social Behavior with End-to-End Data Science

Fine-Grained Arabic Dialect Identification

 

Mental Health as an NLP Problem

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.

 

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).

TitleA family of neural models for voice query understanding on an entertainment platform


Title: Event Semantics in Text Constructions, Vision, and Human-Robot Dialogue

Title: SCRIPTS: a System for Cross Language Information Processing,Translation and Summarization

Abstract: This presentation will give an overview of the research conducted by CLIP students and facuty to develop a System for Cross Language Information Processing, Translation and Summarization, as part of the IARPA MATERIAL program.

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