Huiling You

@conference{eventbased25,

title = {Event-based evaluation of abstractive news summarization},

author = {Huiling You and Samia Touileb and Lilja Øvrelid and Erik Velldal},

url = {https://mediafutures.no/63_event_based_evaluation_of_a/},

year  = {2025},

date = {2025-06-02},

booktitle = {ACL Conference},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{norevent25,

title = {NorEventGen: generative event extraction from Norwegian news},

author = {Huiling You and Samia Touileb and Erik Velldal and Lilja Øvrelid},

url = {https://mediafutures.no/2025_nodalida_1_79/},

year  = {2025},

date = {2025-01-13},

booktitle = {(NoDaLiDa/Baltic-HLT 2025},

abstract = {In this work, we approach event extraction from Norwegian news text using a

generation-based approach, which formulates the task as text-to-structure generation. We present experiments assessing the

effect of different modeling configurations

and provide an analysis of the model predictions and typical system errors. Finally,

we apply our system to a large corpus of

raw news texts and analyze the resulting

distribution of event structures in a fairly

representative snap-shot of the Norwegian

news landscape.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{EDEN,

title = {EDEN: A Dataset for Event Detection in Norwegian News},

author = {Samia Touileb and Jeanett Murstad and Petter Mæhlum and Lubos Steskal and Lilja Charlotte Storset and Huiling You and Lilja Øvrelid},

url = {https://mediafutures.no/2024-lrec-main-488/},

year  = {2024},

date = {2024-05-23},

booktitle = {LREC-COLING 2024},

abstract = {We present EDEN, the first Norwegian dataset annotated with event information at the sentence level, adapting the

widely used ACE event schema to Norwegian. The paper describes the manual annotation of Norwegian text as well

as transcribed speech in the news domain, together with inter-annotator agreement and discussions of relevant

dataset statistics. We also present preliminary modeling results using a graph-based event parser. The resulting

dataset will be made freely available for download and use.

},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}