82 citations · 486 across the 40 of their papers we have counts for
6 papers · 1 filter
Low-Rank RNN Adaptation for Context-Aware Language Modeling
Aaron Jaech, Mari Ostendorf
A context-aware language model uses location, user and/or domain metadata (context) to adapt its predictions. In neural language models, context information is typically represente…
Scientific Information Extraction with Semi-supervised Neural Tagging
Yi Luan, Mari Ostendorf, Hannaneh Hajishirzi
This paper addresses the problem of extracting keyphrases from scientific articles and categorizing them as corresponding to a task, process, or material. We cast the problem as se…
Improving Context Aware Language Models
Aaron Jaech, Mari Ostendorf
Increased adaptability of RNN language models leads to improved predictions that benefit many applications. However, current methods do not take full advantage of the RNN structure…
Reinforcement Learning with External Knowledge and Two-Stage Q-functions for Predicting Popular Reddit Threads
Ji He, Mari Ostendorf, Xiaodong He
This paper addresses the problem of predicting popularity of comments in an online discussion forum using reinforcement learning, particularly addressing two challenges that arise…
Conversation Modeling on Reddit using a Graph-Structured LSTM
Vicky Zayats, Mari Ostendorf
This paper presents a novel approach for modeling threaded discussions on social media using a graph-structured bidirectional LSTM which represents both hierarchical and temporal c…
Parsing Speech: A Neural Approach to Integrating Lexical and Acoustic-Prosodic Information
Trang Tran, Shubham Toshniwal, Mohit Bansal +3
In conversational speech, the acoustic signal provides cues that help listeners disambiguate difficult parses. For automatically parsing spoken utterances, we introduce a model tha…