Papers by Günter Neumann

2 papers
An Interactive Web-Interface for Visualizing the Inner Workings of the Question Answering LSTM (D18-2)

Copied to clipboard

Challenge: Existing visualisation methods for deep learning models are limited by their low interpretability and lack a tool for interpreting them.
Approach: They propose a visualisation tool which plots heatmaps of neurons’ firings and allows a user to check the dependency between neurons and manual features.
Outcome: The proposed visualisation tool plots heatmaps of neurons’ firings and allows a user to check the dependency between neurons and manual features.
Only for the Unseen Languages, Say the Llamas: On the Efficacy of Language Adapters for Cross-lingual Transfer in English-centric LLMs (2025.acl-srw)

Copied to clipboard

Challenge: Most state-of-the-art large language models (LLMs) are trained mainly on English data, limiting their effectiveness on non-English, especially low-resource, languages.
Approach: They train language adapters for 13 languages and evaluate their effectiveness on downstream tasks using either task adapters or in-context learning.
Outcome: The proposed language adapters improve performance for languages not seen during pretraining, but provide negligible benefit for seen languages.

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