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LakeFM is a foundation model for aquatic systems, pre-trained on large-scale ecological datasets to forecast lake dynamics using irregular multivariate multi-depth time series data, achieving competitive performance compared to existing models.
Introduces SciPaths, a benchmark for forecasting the enabling contributions required to realize a target scientific discovery, and evaluates frontier and open-weight language models, finding significant room for improvement in reasoning backward from contributions to enabling building blocks.
MeasHalu is a novel framework for mitigating scientific measurement hallucinations in LLMs through a two-stage reasoning-aware fine-tuning strategy and progressive reward curriculum. It introduces a fine-grained taxonomy of measurement-specific hallucinations and demonstrates improved accuracy on the MeasEval benchmark.