papers

Publications (16)

eess.SY2018

Real-Time Prediction of the Duration of Distribution System Outages

Aaron Jaech, Baosen Zhang, Mari Ostendorf +1

This paper addresses the problem of predicting duration of unplanned power outages, using historical outage records to train a series of neural network predictors. The initial dura…

cs.AI2026

OpenAI o1 System Card

OpenAI, :, Aaron Jaech +261

The o1 model series is trained with large-scale reinforcement learning to reason using chain of thought. These advanced reasoning capabilities provide new avenues for improving the…

cs.CL2016

Domain Adaptation of Recurrent Neural Networks for Natural Language Understanding

Aaron Jaech, Larry Heck, Mari Ostendorf

The goal of this paper is to use multi-task learning to efficiently scale slot filling models for natural language understanding to handle multiple target tasks or domains. The key…

cs.CL2018

Personalized Language Model for Query Auto-Completion

Aaron Jaech, Mari Ostendorf

Query auto-completion is a search engine feature whereby the system suggests completed queries as the user types. Recently, the use of a recurrent neural network language model was…

cs.CL2018

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…

cs.CL2017

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…