activity
20232026
most citedAssessing socio-economic climate impacts from text data

1 citations · 2 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL20261 cited

Assessing socio-economic climate impacts from text data

Mariana Madruga de Brito, Brielen Madureira, Taís Maria Nunes Carvalho +15

Recent advances in natural language processing (NLP) and large language models (LLMs) have enabled the systematic use of large-scale textual data from news, social media, and repor…

cs.CL2025

Climate-Eval: A Comprehensive Benchmark for NLP Tasks Related to Climate Change

Murathan Kurfalı, Shorouq Zahra, Joakim Nivre +1

Climate-Eval is a comprehensive benchmark designed to evaluate natural language processing models across a broad range of tasks related to climate change. Climate-Eval aggregates e…

cs.CL2025

Can LLMs Detect Intrinsic Hallucinations in Paraphrasing and Machine Translation?

Evangelia Gogoulou, Shorouq Zahra, Liane Guillou +2

A frequently observed problem with LLMs is their tendency to generate output that is nonsensical, illogical, or factually incorrect, often referred to broadly as hallucination. Bui…

cs.CL2024

Overview of MWE history, challenges, and horizons: standing at the 20th anniversary of the MWE workshop series via MWE-UD2024

Lifeng Han, Kilian Evang, Archna Bhatia +6

Starting in 2003 when the first MWE workshop was held with ACL in Sapporo, Japan, this year, the joint workshop of MWE-UD co-located with the LREC-COLING 2024 conference marked the…

cs.CL2024

The Hyperfitting Phenomenon: Sharpening and Stabilizing LLMs for Open-Ended Text Generation

Fredrik Carlsson, Fangyu Liu, Daniel Ward +2

This paper introduces the counter-intuitive generalization results of overfitting pre-trained large language models (LLMs) on very small datasets. In the setting of open-ended text…

cs.CL20241 cited

UCxn: Typologically Informed Annotation of Constructions Atop Universal Dependencies

Leonie Weissweiler, Nina Böbel, Kirian Guiller +11

The Universal Dependencies (UD) project has created an invaluable collection of treebanks with contributions in over 140 languages. However, the UD annotations do not tell the full…