Papers by Alexander Henlein

2 papers
On the Influence of Coreference Resolution on Word Embeddings in Lexical-semantic Evaluation Tasks (2020.lrec-1)

Copied to clipboard

Challenge: Existing word embeddings rely on local information delimited by context windows or dependency parents to predict word relations.
Approach: They propose to use coreference resolution to find all spans of a text that refer to the same entity to improve the F1-Scores.
Outcome: The proposed methods do not benefit significantly from pronoun substitution.
What do Toothbrushes do in the Kitchen? How Transformers Think our World is Structured (2022.naacl-main)

Copied to clipboard

Challenge: Recent research reveals that transformer-based models are biased towards extracting knowledge about object relations.
Approach: They propose to use transformer-based models to extract knowledge about object relations to investigate whether they can be used to extract object relations.
Outcome: The proposed models outperform static models in many respects and perform much worse than similarity measures and classifiers.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations