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11/14/2022
Interactively Learning to Summarise Timelines by Reinforcement Learning
Timeline summarisation (TLS) aims to create a time-ordered summary list ...
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08/31/2022
Efficient Methods for Natural Language Processing: A Survey
Getting the most out of limited resources allows advances in natural lan...
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09/02/2021
Ranking Scientific Papers Using Preference Learning
Peer review is the main quality control mechanism in academia. Quality o...
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10/23/2020
Ranking Creative Language Characteristics in Small Data Scenarios
The ability to rank creative natural language provides an important gene...
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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...
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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...
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04/30/2020
Generating Persona-Consistent Dialogue Responses Using Deep Reinforcement Learning
Recent transformer-based open-domain dialogue agents are trained by refe...
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12/04/2019
Scalable Bayesian Preference Learning for Crowds
We propose a scalable Bayesian preference learning method for jointly pr...
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04/05/2019
Bayesian Heatmaps: Probabilistic Classification with Multiple Unreliable Information Sources
Unstructured data from diverse sources, such as social media and aerial ...
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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...
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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...
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06/06/2018
