2 research outputs found
Enhancing Lifelong Language Learning by Improving Pseudo-Sample Generation
To achieve lifelong language learning, pseudo-rehearsal methods leverage samples generated from a language model to refresh the knowledge of previously learned tasks. Without proper controls, however, these methods could fail to retain the knowledge of complex tasks with longer texts since most of the generated samples are low in quality. To overcome the problem, we propose three specific contributions. First, we utilize double language models, each of which specializes in a specific part of the input, to produce high-quality pseudo samples. Second, we reduce the number of parameters used by applying adapter modules to enhance training efficiency. Third, we further improve the overall quality of pseudo samples using temporal ensembling and sample regeneration. The results show that our framework achieves significant improvement over baselines on multiple task sequences. Also, our pseudo sample analysis reveals
helpful insights for designing even better pseudo-rehearsal methods in the future
SUMO User Conference 2019
SUMO2019:Editor's Preface
This volume contains the papers presented at the SUMO Conference 2019 Simulating Connected Urban Mobility. The conference was held in Berlin from 13-15 May 2019. The goal of the conference was to present new results in the field of mobility simulation and modelling using traffic tools and data which are open available.There were 32 submissions. Each submission was reviewed by at least 2 program committee members. The committee decided to accept 22 papers.
Traffic simulations have a high value for traffic research studies. New traffic strategies can be tested and evaluated in advance with little costs. For realistic simulation results a complex traffic simulation framework is needed. One microscopic traffic simulation for this purpose is the open source tool Eclipse SUMO (Simulation of open mobility) which is available since 2001. SUMO provides a wide range of transport planning and modelling applications.
The major topic of the 7th SUMO conference is the simulation of connected vehicles. This volume contains articles about simulator coupling, connected and automated Vehicles. Furthermore, the journal includes also papers about new algorithms for traffic light systems and new applications for the simulation of other traffic modes or reinforcement learning strategies.
We would like to thank EasyChair for the conference support and its helpfull conference management tool.
Laura Bieker-Walz
Melanie Weber
Robert Hilbrich
Michael Behrisch
July 24, 2019
Berli