Samuel Dahan

According to our database, Samuel Dahan authored at least 10 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2023

Towards Legally Enforceable Hate Speech Detection for Public Forums.

Chu Fei Luo, Rohan Bhambhoria, Xiaodan Zhu, Samuel Dahan

CoRR, 2023

OpenJustice.ai: A Global Open-Source Legal Language Model.

Samuel Dahan, Rohan Bhambhoria, David Liang, Xiaodan Zhu

Proceedings of the Legal Knowledge and Information Systems, 2023

Legally Enforceable Hate Speech Detection for Public Forums.

Chu Fei Luo, Rohan Bhambhoria, Samuel Dahan, Xiaodan Zhu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Prototype-Based Interpretability for Legal Citation Prediction.

Chu Fei Luo, Rohan Bhambhoria, Samuel Dahan, Xiaodan Zhu

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Evaluating Explanation Correctness in Legal Decision Making.

Chu Fei Luo, Rohan Bhambhoria, Samuel Dahan, Xiaodan Zhu

Proceedings of the 35th Canadian Conference on Artificial Intelligence, Toronto, Ontario, 2022

Interpretable Low-Resource Legal Decision Making.

Rohan Bhambhoria, Hui Liu, Samuel Dahan, Xiaodan Zhu

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Detection of Similar Legal Cases on Personal Injury.

Jason T. Lam, Yuhao Chen, Farhana H. Zulkernine, Samuel Dahan

Proceedings of the 2021 International Conference on Data Mining, 2021

Investigating the State-of-the-Art Performance and Explainability of Legal Judgment Prediction.

Rohan Bhambhoria, Samuel Dahan, Xiaodan Zhu

Proceedings of the 34th Canadian Conference on Artificial Intelligence, 2021

2020

The Gap between Deep Learning and Law: Predicting Employment Notice.

Jason T. Lam, David Liang, Samuel Dahan, Farhana H. Zulkernine

Proceedings of the Natural Legal Language Processing Workshop 2020 co-located with the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2020), 2020

Determining Worker Type from Legal Text Data using Machine Learning.

Yifei Yin, Farhana H. Zulkernine, Samuel Dahan

Proceedings of the IEEE Intl Conf on Dependable, 2020