Retrieval-Augmented Classification of Environmental Mitigations in Hydropower Licensing Documents
Identifying and classifying environmental mitigation obligations in Federal Energy Regulatory Commission hydropower licensing documents is a labor-intensive task requiring deep domain expertise. We formulate this as a multi-label classification problem over a structured 135-category taxonomy and address the central challenge of severe label scarcity: 40 of 135 categories have no training examples, and 26 have fewer than five. A supervised Bidirectional Encoder Representations from Transformers (BERT)-based pipeline, while effective on well-represented categories, achieves F1 of zero on unseen classes regardless of augmentation strategy. We introduce a Retrieval-Augmented Generation (RAG) ...
| Authors | Hong-Jun Yoon, Tom Ruggles, Joanna Lee et al. |
|---|---|
| Primary category | cs.IR |
| Published | 24 August 2026 |
| Last updated at source | 24 August 2026 |
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