Papers by Damián Furman

2 papers
High-quality argumentative information in low resources approaches improve counter-narrative generation (2023.findings-emnlp)

Copied to clipboard

Challenge: a recent study shows that fine-tuning improves the performance of language models . large language models generate acceptable texts in a number of scenarios, a study shows .
Approach: They show that fine-tuning improves the task of hate speech counter-narrative generation . they provide a subset of arguments and a good base model is required for the fine-uning to have a positive impact.
Outcome: The proposed model produces counter-narratives that are as satisfactory as the whole set.
MessIRve: A Large-Scale Spanish Information Retrieval Dataset (2025.emnlp-main)

Copied to clipboard

Challenge: Information retrieval (IR) is the task of finding relevant documents in response to a user query.
Approach: They propose a large-scale Spanish IR dataset with almost 700,000 queries from Google’s autocomplete API and relevant documents sourced from Wikipedia.
Outcome: The proposed dataset covers a wide variety of topics, unlike smaller datasets.

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