Papers by Søren Fomsgaard

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Papers by Søren Fomsgaard

ACL

2026.acl-long

DPO
in-context learning
automated evaluators
GPT-4o-mini
editing rates
mitigating online polarization
high-quality generation
Direct Preference Optimization
non-English neutralization
seq2seq

2026

Language Models

1 papers

Par-ITA: Benchmarking Seq2Seq and LLMs on a Human-Supervised Parallel Corpus for Italian Hyperpartisan Neutralization (2026.acl-long)

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Michele Joshua Maggini, Søren Fomsgaard, Michele Maestroni, Gaël Dias, Pablo Gamallo

Language Models

Challenge:	a new study examines the role of hyperpartisan content in online polarization in the social web.
Approach:	They propose a human-supervised parallel corpus for italian hyperpartisan neutralization of 2,475 paragraph pairs.
Outcome:	The proposed dataset is the first human-supervised parallel corpus for italian hyperpartisan neutralization of 2,475 paragraph pairs.

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