Papers by Jon Atle Gulla

3 papers
NLEBench+NorGLM: A Comprehensive Empirical Analysis and Benchmark Dataset for Generative Language Models in Norwegian (2024.emnlp-main)

Copied to clipboard

Challenge: Norwegian is under-represented within the most impressive breakthroughs in NLP tasks.
Approach: they investigate the impact of existing Norwegian language models on Norwegian generation tasks . they pre-trained 4 Norwegian Open Language Models from parameter scales and architectures .
Outcome: The proposed benchmark evaluates the performance of language models on Norwegian generation tasks.
Building Sentiment Lexicons for Mainland Scandinavian Languages Using Machine Translation and Sentence Embeddings (2022.lrec-1)

Copied to clipboard

Challenge: a simple but effective method to build sentiment lexicons for the three Mainland Scandinavian languages is proposed . a number of experiments with Scandinavian language datasets yield state-of-the-art results using a rule-based sentiment analysis algorithm.
Approach: They propose a simple but effective method to build sentiment lexicons for the three Mainland Scandinavian languages.
Outcome: The proposed method is based on the English Sentiwordnet and a thesaurus in one of the target languages.
Balancing Multi-Domain Corpora Learning for Open-Domain Response Generation (2022.findings-naacl)

Copied to clipboard

Challenge: Existing studies on open-domain conversational systems are limited to single corpus training and evaluation.
Approach: They propose a method which encodes each corpus through a unique corpus embedding and a new word-level importance weighting method that integrates DF to the loss function.
Outcome: The proposed methods gain significant improvements on both automatic and human evaluation.

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