An accurate and substantial dataset is necessary to train a reliable and...
Memes are a popular form of communicating trends and ideas in social med...
In behavioural testing, system functionalities underrepresented in the
s...
Self-supervised knowledge-graph completion (KGC) relies on estimating a
...
We propose to use reinforcement learning to inform transformer-based
con...
In the weakly supervised learning paradigm, labeling functions automatic...
Weak supervision is leveraged in a wide range of domains and tasks due t...
Collections of research article data harvested from the web have become
...
In recent years, deep neural language models have made strong progress i...
A popular approach to decrease the need for costly manual annotation of ...
A way to overcome expensive and time-consuming manual data labeling is w...
Behavioural testing – verifying system capabilities by validating
human-...
We propose a scheme for self-training of grammaticality models for
const...
The absence of labeled data for training neural models is often addresse...
Welcome to WeaSuL 2021, the First Workshop on Weakly Supervised Learning...
We propose new methods for in-domain and cross-domain Named Entity
Recog...
Methods for improving the training and prediction quality of weakly
supe...
Nowadays, classical count-based word embeddings using positive pointwise...
Interpretability of machine learning (ML) models becomes more relevant w...
The performance of a Part-of-speech (POS) tagger is highly dependent on ...
Count-based word alignment methods, such as the IBM models or fast-align...
Input optimization methods, such as Google Deep Dream, create interpreta...
In this work, we propose a new model for aspect-based sentiment analysis...
This paper describes how to apply self-attention with relative positiona...
Semi-supervised bootstrapping techniques for relationship extraction fro...
In this work, we introduce the task of Open-Type Relation Argument Extra...
We propose two novel paradigms for evaluating neural network explanation...
We address relation classification in the context of slot filling, the t...
Universal schema builds a knowledge base (KB) of entities and relations ...
Knowledge base (KB) completion adds new facts to a KB by making inferenc...