research
∙
11/14/2022
Interactively Learning to Summarise Timelines by Reinforcement Learning
Timeline summarisation (TLS) aims to create a time-ordered summary list ...
share
research
∙
08/31/2022
Efficient Methods for Natural Language Processing: A Survey
Getting the most out of limited resources allows advances in natural lan...
research
∙
09/02/2021
Ranking Scientific Papers Using Preference Learning
Peer review is the main quality control mechanism in academia. Quality o...
research
∙
10/23/2020
Ranking Creative Language Characteristics in Small Data Scenarios
The ability to rank creative natural language provides an important gene...
research
∙
08/03/2020
OFAI-UKP at HAHA@IberLEF2019: Predicting the Humorousness of Tweets Using Gaussian Process Preference Learning
Most humour processing systems to date make at best discrete, coarse-gra...
research
∙
05/01/2020
Low Resource Multi-Task Sequence Tagging – Revisiting Dynamic Conditional Random Fields
We compare different models for low resource multi-task sequence tagging...
research
∙
04/30/2020
Generating Persona-Consistent Dialogue Responses Using Deep Reinforcement Learning
Recent transformer-based open-domain dialogue agents are trained by refe...
research
∙
12/04/2019
Scalable Bayesian Preference Learning for Crowds
We propose a scalable Bayesian preference learning method for jointly pr...
research
∙
04/05/2019
Bayesian Heatmaps: Probabilistic Classification with Multiple Unreliable Information Sources
Unstructured data from diverse sources, such as social media and aerial ...
research
∙
03/27/2019
Text Processing Like Humans Do: Visually Attacking and Shielding NLP Systems
Visual modifications to text are often used to obfuscate offensive comme...
research
∙
11/02/2018
Bayesian Ensembles of Crowds and Deep Learners for Sequence Tagging
Current methods for sequence tagging, a core task in NLP, are data hungr...
research
∙
06/06/2018