Fetching the paper…
Reading the bibliography…
How objective and unbiased are we while making decisions? This work investigates cognitive bias identification in high-stake decision making process by human experts, questioning its effectiveness in real-world settings, such as candidates assessments for university admission.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Pruning and Sparsemax Methods for Hierarchical Attention Networks
João G Ribeiro, Frederico S Felisberto, and Isabel C Neto. 2020 · 2004
Earlier work this paper cites.
Learning phrase representations using RNN encoder–decoder for statistical machine translation. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) . 1724–1734
Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Machine Bias: There’s software used across the country to predict future criminals. And it’s biased against blacks
Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner. 2016 · 2016
Earlier work this paper cites.
Learning identity mappings with residual gates
Pedro HP Savarese, Leonardo O Mazza, and Daniel R Figueiredo. 2016 · 2016
Earlier work this paper cites.
Hierarchical attention networks for document classification. In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . 1480–1489
Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, and Eduard Hovy. 2016a · 2016
Earlier work this paper cites.
Hierarchical attention networks for document classification. In Proceedings of the 2016 conference of the North American chapter of the association for computational linguistics: human language technologies . 1480–1489
Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, and Eduard Hovy. 2016b · 2016
Earlier work this paper cites.
Attention is all you need
A Vaswani. 2017 · 2017
Earlier work this paper cites.
Attention is all you need. In Advances in Neural Information Processing Systems , Vol. 30
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
The accuracy, fairness, and limits of predicting recidivism
Julia Dressel and Hany Farid. 2018 · 2018
Earlier work this paper cites.
BERT: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . 4171–4186
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Cross-lingual language model pretraining. In Advances in Neural Information Processing Systems , Vol. 32
Guillaume Lample and Alexis Conneau. 2019 · 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 · 2019
Cited alongside, same era.
Cognitive bias, decision styles, and risk attitudes in decision making and DSS
Gloria Phillips-Wren, Daniel J Power, and Manuel Mora. 2019b · 2019
Cited alongside, same era.
D-BIAS: A Causality-Based Human-in-the-Loop System for Tackling Algorithmic Bias
Auditing for human expertise
Rohan Alur, Loren Laine, Darrick Li, Manish Raghavan, Devavrat Shah, and Dennis Shung. 2024 · 2024
Closest in time.
The Claude 3 Model Family: Opus, Sonnet, Haiku
Anthropic. 2024 · 2024
Closest in time.
Matthijs Douze, Alexandr Guzhva, Chengqi Deng, Jeff Johnson, Gergely Szilvasy, Pierre-Emmanuel Mazaré, Maria Lomeli, Lucas Hosseini, and Hervé Jégou. 2024 · 2024
Closest in time.
Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al · 2024
Closest in time.
Cognitive Bias in High-Stakes Decision-Making with LLMs
Jessica Echterhoff and et al. 2024 · 2024
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Bhavya Ghai and Klaus Mueller. 2022 · 2022
Cited alongside, same era.
Title2Vec: a contextual job title embedding for occupational named entity recognition and other applications
Junhua Liu, Yung Chuen Ng, Zitong Gui, Trisha Singhal, Lucienne T. M. Blessing, Kristin L. Wood, and Kwan Hui Lim. 2022 · 2022
Cited alongside, same era.
A Statistical Perspective on Retrieval-Based Models. In Proceedings of the 40th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 202) , Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, and Jonathan Scarlett (Eds.). PMLR, 1852–1886
Soumya Basu, Ankit Singh Rawat, and Manzil Zaheer. 2023 · 2023
Cited alongside, same era.
Cognitive Bias and How to Improve Sustainable Decision Making
D. Kahneman and A. Tversky. 2023 · 2023
Cited alongside, same era.
A Formal Perspective on Byte-Pair Encoding. In Findings of the Association for Computational Linguistics: ACL 2023 , Anna Rogers, Jordan Boyd-Graber, and Naoaki Okazaki (Eds.). Association for Computational Linguistics, Toronto, Canada, 598–614
Vilém Zouhar, Clara Meister, Juan Gastaldi, Li Du, Tim Vieira, Mrinmaya Sachan, and Ryan Cotterell. 2023 · 2023
Cited alongside, same era.
Cognitive bias, decision styles, and risk attitudes in decision making and DSS
Gloria Phillips-Wren, Daniel J Power, and Manuel Mora. 2019a
Cited in the paper.
Overcoming Anchoring Bias: The Potential of AI and XAI-based Decision Support
Felix Haag, Carlo Stingl, Katrin Zerfass, Konstantin Hopf, and Thorsten Staake. 2024 · 2024
Closest in time.
OpenAI. 2024 · 2024
Closest in time.
Bias and Fairness in High-Stakes AI: Challenges of Data Sensitivity and Access
John Smith, Jane Doe, and Andrew Lee. 2024 · 2024
Closest in time.
Fair Machine Guidance to Enhance Fair Decision Making in Biased People
Mingzhe Yang and et al. 2024 · 2024
Closest in time.