Papers by Patrick Brandt
ConfliBERT: A Pre-trained Language Model for Political Conflict and Violence (2022.naacl-main)
Copied to clipboard
Yibo Hu, MohammadSaleh Hosseini, Erick Skorupa Parolin, Javier Osorio, Latifur Khan, Patrick Brandt, Vito D’Orazio
| Challenge: | Traditionally, researchers used manual coding to track conflict processes worldwide, but the high costs and slow pace of domain experts make it difficult and costly to monitor complex and rapidly changing conflicts. |
| Approach: | They propose a domain-specific pre-trained language model for conflict and political violence that can be used to train a language model from scratch and continue training. |
| Outcome: | The proposed model outperforms BERT in conflict research. |
Leveraging Codebook Knowledge with NLI and ChatGPT for Zero-Shot Political Relation Classification (2024.acl-long)
Copied to clipboard
| Challenge: | Existing annotation codebook is labor-intensive for coding events from large datasets. |
| Approach: | They propose to use existing annotation codebook to classify political relations without extensive annotations. |
| Outcome: | The proposed methods outperform dictionary-based methods and the existing ontology annotation codebook and improve interpretability and efficiency. |