Fetching the paper…
Reading the bibliography…
Peer-to-peer (P2P) lending connects borrowers and lenders through online platforms but suffers from significant information asymmetry, as lenders often lack sufficient data to assess borrowers' creditworthiness.
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence
John H. Holland · 1992
Earlier work this paper cites.
Tell me a good story and I may lend you my money: The role of narratives in peer-to-peer lending decisions
Michal Herzenstein, Scott Sonenshein, and Utpal M. Dholakia · 2011
Earlier work this paper cites.
When is a liability not a liability? Textual analysis, dictionaries, and 10-Ks
Tim Loughran and Bill McDonald · 2011
Earlier work this paper cites.
Do unverifiable disclosures matter? Evidence from peer-to-peer lending
Jeremy Michels · 2012
Earlier work this paper cites.
Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
Earlier work this paper cites.
Fast implementation of DeLong’s algorithm for comparing the areas under correlated receiver operating characteristic curves
Xu Sun and Weichao Xu · 2014
Earlier work this paper cites.
Lemon or cherry? The value of texts in debt crowdfunding
Qiang Gao and Mingfeng Lin · 2015
Earlier work this paper cites.
XGBoost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin · 2016
Earlier work this paper cites.
Description-text related soft information in peer-to-peer lending – Evidence from two leading European platforms
Gregor Dorfleitner, Christopher Priberny, Stephanie Schuster, Johannes Stoiber, Martina Weber, Ivan de Castro, and Julia Kammler · 2016
Earlier work this paper cites.
”Why Should I Trust You?”: Explaining the predictions of any classifier
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin · 2016
Earlier work this paper cites.
Credit risk evaluation based on text analysis
Shuxia Wang, Yuwei Qi, Bin Fu, and Hongzhi Liu · 2016
Earlier work this paper cites.
Identifying features for detecting fraudulent loan requests on p2p platforms
Jennifer Xu, Dongyu Chen, and Michael Chau · 2016
Earlier work this paper cites.
Loan default prediction by combining soft information extracted from descriptive text in online peer-to-peer lending
Cuiqing Jiang, Zhao Wang, Ruiya Wang, and Yong Ding · 2017
Earlier work this paper cites.
A unified approach to interpreting model predictions
Scott M. Lundberg and Su-In Lee · 2017
Earlier work this paper cites.
Attention Is All You Need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Cost-sensitive boosted tree for loan evaluation in peer-to-peer lending
Yufei Xia, Chuanzhe Liu, and Nana Liu · 2017
Earlier work this paper cites.
Addressing Information Asymmetries in Online Peer-to-Peer Lending. In Disrupting Finance
Mark Cummins, Theo Lynn, Ciarán Mac an Bhaird, and Pierangelo Rosati · 2018
Earlier work this paper cites.
Network topology and systemic risk in peer-to-peer lending market
Yuelei Li, Aiting Hao, Xiaotao Zhang, and Xiong Xiong · 2018
Earlier work this paper cites.
Catboost: unbiased boosting with categorical features
Liudmila Prokhorenkova, Gleb Gusev, Aleksandr Vorobev, Anna Veronika Dorogush, and Andrey Gulin · 2018
Earlier work this paper cites.
Anchors: high-precision model-agnostic explanations
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin · 2018
Earlier work this paper cites.
The relationship between soft information in loan titles and online peer-to-peer lending: evidence from renrendai platform
Jianrong Yao, Jiarui Chen, June Wei, Yuangao Chen, and Shuiqing Yang · 2018
Earlier work this paper cites.
Loan evaluation in p2p lending based on random forest optimized by genetic algorithm with profit score
Xin Ye, Lu an Dong, and Da Ma · 2018
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
Cited alongside, same era.
Target-dependent sentiment classification with BERT
Zhengjie Gao, Ao Feng, Xinyu Song, and Xi Wu · 2019
Cited alongside, same era.
Sarthak Jain and Byron C. Wallace · 2019
Cited alongside, same era.
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut · 2019
Cited alongside, same era.
Credit risk evaluation model with textual features from loan descriptions for p2p lending
Weiguo Zhang, Chao Wang, Yue Zhang, and Junbo Wang · 2020
Later among the works it cites.
Online peer-to-peer lending: A review of the literature
Shabeen A. Basha, Mohammed M. Elgammal, and Bana M. Abuzayed · 2021
Later among the works it cites.
Risk-return modelling in the p2p lending market: Trends, gaps, recommendations and future directions
Miller-Janny Ariza-Garzón, María-Del-Mar Camacho-Miñano, María-Jesús Segovia-Vargas, and Javier Arroyo · 2021
Later among the works it cites.
Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Greg Brockman, Alex Ray, et al · 2021
Later among the works it cites.
The value of text for small business default prediction: A Deep Learning approach
Matthew Stevenson, Christophe Mues, and Cristián Bravo · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang · 2019
Cited alongside, same era.
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer · 2019
Cited alongside, same era.
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2019
Cited alongside, same era.
Thirty recommendations on regulation, innovation and finance. final report to the european commission by the expert group on regulatory obstacles to financial innovation
ROFIEG · 2019
Cited alongside, same era.
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf · 2019
Cited alongside, same era.
Is attention interpretable?
Sofia Serrano and Noah A. Smith · 2019
Cited alongside, same era.
New explainability method for BERT-based model in fake news detection
Mateusz Szczepański, Marek Pawlicki, Rafał Kozik, and Michał Choraś · 2021
Later among the works it cites.
Prompted opinion summarization with GPT-3.5
Adithya Bhaskar, Alexander R Fabbri, and Greg Durrett · 2022
Later among the works it cites.
Bertopic: Neural topic modeling with a class-based tf-idf procedure
Maarten Grootendorst · 2022
Later among the works it cites.
Credit default prediction from user-generated text in peer-to-peer lending using deep learning
Johannes Kriebel and Lennart Stitz · 2022
Later among the works it cites.
Post-hoc interpretability for neural NLP: A survey
Andreas Madsen, Siva Reddy, and Sarath Chandar · 2022
Later among the works it cites.
Do facial images matter? Understanding the role of private information disclosure in crowdfunding markets
Zhiyuan Qi, Dongyu Chen, and Jennifer J. Xu · 2022
Later among the works it cites.
Universal spam detection using transfer learning of BERT model
Vijay Srinivas Tida and Sonya Hy Hsu · 2022
Later among the works it cites.
Peer-to-peer loan fraud detection: Constructing features from transaction data
Jennifer Xu, Dongyu Chen, Michael Chau, Liting Li, and Haichao Zheng · 2022
Later among the works it cites.
David Pride, Matteo Cancellieri, and Petr Knoth · 2023
Later among the works it cites.
Peer-to-peer (p2p) lending risk management: Assessing credit risk on social lending platforms using textual factors
Michael Siering · 2023
Later among the works it cites.
Text classification via large language models
Xiaofei Sun, Xiaoya Li, Jiwei Li, Fei Wu, Shangwei Guo, Tianwei Zhang, and Guoyin Wang · 2023
Later among the works it cites.
Extracting narrative data via large language models for loan default prediction: when talk isn’t cheap
Yufei Xia, Zhengxu Shi, Xiaoying Du, and Qiong Zheng · 2023
Later among the works it cites.
Profit-sensitive machine learning classification with explanations in credit risk: The case of small businesses in peer-to-peer lending
Miller-Janny Ariza-Garzón, Javier Arroyo, María-Jesús Segovia-Vargas, and Antonio Caparrini · 2024
Closest in time.
Lending Club loan dataset for granting models, May 2024
Miller Janny Ariza-Garzón, Mario Sanz-Guerrero, Javier Arroyo Gallardo, and Lending Club · 2024
Closest in time.
Advancing credit risk modelling with machine learning: A comprehensive review of the state-of-the-art
André Aoun Montevechi, Rafael de Carvalho Miranda, André Luiz Medeiros, and José Arnaldo Barra Montevechi · 2024
Closest in time.