1 citations · 1 across the 1 of their papers we have counts for
6 papers
Assessing socio-economic climate impacts from text data
Mariana Madruga de Brito, Brielen Madureira, TaÃs 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…
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…
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…
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…
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…
Continual Learning Under Language Shift
Evangelia Gogoulou, Timothée Lesort, Magnus Boman +1
The recent increase in data and model scale for language model pre-training has led to huge training costs. In scenarios where new data become available over time, updating a model…