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Over the recent years, large pretrained language models (LM) have revolutionized the field of natural language processing (NLP).
Finbert: Financial sentiment analysis with pre-trained language models
Araci, D. 2019 · 1908
Earlier work this paper cites.
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Sanh, V.; Debut, L.; Chaumond, J.; and Wolf, T. 2019 · 1910
Earlier work this paper cites.
A Unified Architecture for Natural Language Processing: Deep Neural Networks with Multitask Learning
Collobert, R.; and Weston, J. 2008 · 2008
Earlier work this paper cites.
Chalkidis, I.; Fergadiotis, M.; Malakasiotis, P.; Aletras, N.; and Androutsopoulos, I. 2020 · 2010
Earlier work this paper cites.
Artificial intelligence measurement of disclosure (AIMD)
Grüning, M. 2011 · 2011
Earlier work this paper cites.
Analyzing Sustainability Reports Using Natural Language Processing
Luccioni, A.; Baylor, E.; and Duchene, N. 2020 · 2011
Earlier work this paper cites.
CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims
Diggelmann, T.; Boyd-Graber, J.; Bulian, J.; Ciaramita, M.; and Leippold, M. 2020 · 2012
Earlier work this paper cites.
Climate Change Sentiment on Twitter: An Unsolicited Public Opinion Poll
Cody, E. M.; Reagan, A. J.; Mitchell, L.; Dodds, P. S.; and Danforth, C. M. 2015 · 2015
Earlier work this paper cites.
Aligning books and movies: Towards story-like visual explanations by watching movies and reading books
Zhu, Y.; Kiros, R.; Zemel, R.; Salakhutdinov, R.; Urtasun, R.; Torralba, A.; and Fidler, S. 2015 · 2015
Earlier work this paper cites.
Learning to select data for transfer learning with Bayesian Optimization
Ruder, S.; and Plank, B. 2017 · 2017
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2018 · 2018
Cited alongside, same era.
Universal Language Model Fine-tuning for Text Classification
Howard, J.; and Ruder, S. 2018 · 2018
Cited alongside, same era.
Analysis of Recognition of Climate Changes using Word2Vec
Kim, D.-Y.; and Kang, S.-W. 2018 · 2018
Cited alongside, same era.
Transformer-XL: Attentive Language Models beyond a Fixed-Length Context
Dai, Z.; Yang, Z.; Yang, Y.; Carbonell, J. G.; Le, Q.; and Salakhutdinov, R. 2019 · 2019
Cited alongside, same era.
OpenWebText Corpus
Gokaslan, A.; and Cohen, V. 2019 · 2019
Cited alongside, same era.
ClimaText: A dataset for climate change topic detection
Varini, F. S.; Boyd-Graber, J.; Ciaramita, M.; and Leippold, M. 2020 · 2020
Later among the works it cites.
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?
Bender, E. M.; Gebru, T.; McMillan-Major, A.; and Shmitchell, S. 2021 · 2021
Closest in time.
Systematic mapping of global research on climate and health: a machine learning review
Berrang-Ford, L.; Sietsma, A. J.; Callaghan, M.; Minx, J. C.; Scheelbeek, P. F.; Haddaway, N. R.; Haines, A.; and Dangour, A. D. 2021 · 2021
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Machine-learning-based evidence and attribution mapping of 100,000 climate impact studies
Callaghan, M.; Schleussner, C.-F.; Nath, S.; Lejeune, Q.; Knutson, T. R.; Reichstein, M.; Hansen, G.; Theokritoff, E.; Andrijevic, M.; Brecha, R. J.; et al. 2021 · 2021
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Automated Identification of Climate Risk Disclosures in Annual Corporate Reports
Friederich, D.; Kaack, L. H.; Luccioni, A.; and Steffen, B. 2021 · 2021
Closest in time.
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Trinh, T. H.; and Le, Q. V. 2019 · 2019
Cited alongside, same era.
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
Clark, K.; Luong, M.-T.; Le, Q. V.; and Manning, C. D. 2020 · 2020
Cited alongside, same era.
Don’t Stop Pretraining: Adapt Language Models to Domains and Tasks
Gururangan, S.; Marasović, A.; Swayamdipta, S.; Lo, K.; Beltagy, I.; Downey, D.; and Smith, N. A. 2020 · 2020
Cited alongside, same era.
Ask BERT: How regulatory disclosure of transition and physical climate risks affects the CDS term structure
Kölbel, J. F.; Leippold, M.; Rillaerts, J.; and Wang, Q. 2020 · 2020
Cited alongside, same era.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
Lee, J.; Yoon, W.; Kim, S.; Kim, D.; Kim, S.; So, C. H.; and Kang, J. 2020 · 2020
Cited alongside, same era.
Cheap talk and cherry-picking: What ClimateBert
Bingler, J. A.; Kraus, M.; Leippold, M.; and Webersinke, N. 2022a
Cited in the paper.
Cheap talk in corporate climate commitments: The role of active institutional ownership, signaling, materiality, and sentiment
Bingler, J. A.; Kraus, M.; Leippold, M.; and Webersinke, N. 2022b
Cited in the paper.
Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction
Rasmy, L.; Xiang, Y.; Xie, Z.; Tao, C.; and Zhi, D. 2021 · 2021
Closest in time.
Evidence based Automatic Fact-Checking for Climate Change Misinformation
Wang, G.; Chillrud, L.; and McKeown, K. 2021 · 2021
Closest in time.
Towards Climate Awareness in NLP Research
Hershcovich, D.; Webersinke, N.; Kraus, M.; Bingler, J. A.; and Leippold, M. 2022 · 2022
Closest in time.
Firm-level Climate Change Exposure
Sautner, Z.; van Lent, L.; Vilkov, G.; and Zhang, R. 2022 · 2022
Closest in time.
A Dataset for Detecting Real-World Environmental Claims
Stammbach, D.; Webersinke, N.; Bingler, J. A.; Kraus, M.; and Leippold, M. 2022 · 2022
Closest in time.