Efficient methods for natural language processing: A survey

M Treviso, JU Lee, T Ji, B Aken, Q Cao… - Transactions of the …, 2023 - direct.mit.edu
Recent work in natural language processing (NLP) has yielded appealing results from
scaling model parameters and training data; however, using only scale to improve …

Foundation models for weather and climate data understanding: A comprehensive survey

S Chen, G Long, J Jiang, D Liu, C Zhang - arXiv preprint arXiv:2312.03014, 2023 - arxiv.org
As artificial intelligence (AI) continues to rapidly evolve, the realm of Earth and atmospheric
sciences is increasingly adopting data-driven models, powered by progressive …

Climatebert: A pretrained language model for climate-related text

N Webersinke, M Kraus, JA Bingler… - arXiv preprint arXiv …, 2021 - arxiv.org
Over the recent years, large pretrained language models (LM) have revolutionized the field
of natural language processing (NLP). However, while pretraining on general language has …

Where and how machine learning plays a role in climate finance research

A Alonso-Robisco, J Bas, JM Carbo… - … Finance & Investment, 2024 - Taylor & Francis
The financial sector, by mobilizing capital, is fundamental to adapt and mitigate the impact of
climate change in the economy. This has led to the emergence of a new research field …

Data-centric green artificial intelligence: A survey

S Salehi, A Schmeink - IEEE Transactions on Artificial …, 2023 - ieeexplore.ieee.org
With the exponential growth of computational power and the availability of large-scale
datasets in recent years, remarkable advancements have been made in the field of artificial …

Enhancing large language models with climate resources

M Kraus, JA Bingler, M Leippold, T Schimanski… - arXiv preprint arXiv …, 2023 - arxiv.org
Large language models (LLMs) have significantly transformed the landscape of artificial
intelligence by demonstrating their ability in generating human-like text across diverse …

Efficiency is not enough: A critical perspective of environmentally sustainable AI

D Wright, C Igel, G Samuel, R Selvan - arXiv preprint arXiv:2309.02065, 2023 - arxiv.org
Artificial Intelligence (AI) is currently spearheaded by machine learning (ML) methods such
as deep learning (DL) which have accelerated progress on many tasks thought to be out of …

Must NLP be Extractive?

S Bird - 62nd Annual Meeting of the Association for …, 2024 - researchers.cdu.edu.au
How do we roll out language technologies across a world with 7,000 languages? In one
story, we scale the successes of NLP further into'low-resource'languages, doing ever more …

[HTML][HTML] How cheap talk in climate disclosures relates to climate initiatives, corporate emissions, and reputation risk

JA Bingler, M Kraus, M Leippold… - Journal of Banking & …, 2024 - Elsevier
Navigating the complex landscape of corporate climate disclosures and their real impacts is
crucial for managing climate-related financial risks. However, current disclosures oftentimes …

Evaluating text classification: A benchmark study

M Reusens, A Stevens, J Tonglet, J De Smedt… - Expert Systems with …, 2024 - Elsevier
This paper presents an impartial and extensive benchmark for text classification involving
five different text classification tasks, 20 datasets, 11 different model architectures, and …