Fully trained BiLSTM outperforms zero-shot and LoRA-adapted TSFMs on California wildfire PM2.5 under leave-one-incident-out evaluation, especially at hazardous AQI thresholds.
The changing risk and burden of wildfire in the United States.Proceedings of the National Academy of Sciences, 118(2), 2021
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Evaluating the Generalizability of Foundation Models for Extreme Environmental Events: Case Study of California Wildfire PM2.5
Fully trained BiLSTM outperforms zero-shot and LoRA-adapted TSFMs on California wildfire PM2.5 under leave-one-incident-out evaluation, especially at hazardous AQI thresholds.