Search Results for author:
Found 7 papers, 3 papers with code
Using NLP to quantify the environmental cost and diversity benefits of in-person NLP conferences
The environmental costs of research are progressively important to the NLP community and their associated challenges are increasingly debated.
Verifying the Robustness of Automatic Credibility Assessment
Text classification methods have been widely investigated as a way to detect content of low credibility: fake news, social media bots, propaganda, etc.
PolQA: Polish Question Answering Dataset
Recently proposed systems for open-domain question answering (OpenQA) require large amounts of training data to achieve state-of-the-art performance.
Deanthropomorphising NLP: Can a Language Model Be Conscious?
However, here we take the position that such a large language model cannot be sentient, or conscious, and that LaMDA in particular exhibits no advances over other similar models that would qualify it.
Investigating Text Simplification Evaluation
Modern text simplification (TS) heavily relies on the availability of gold standard data to build machine learning models.
How big is big enough? Unsupervised word sense disambiguation using a very large corpus
In this paper, the problem of disambiguating a target word for Polish is approached by searching for related words with known meaning.
Boosting Question Answering by Deep Entity Recognition
In this paper an open-domain factoid question answering system for Polish, RAFAEL, is presented.
