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DiscoPER not only automates hypothesis generation but also self-analyzes its discoveries, revealing hidden patterns and expanding the search space in unprecedented ways.
Automated identification of individual animals can only be effective if it aligns with ecological questions and data practices, not just algorithmic accuracy.
Forget complex selection algorithms: gradient-based data representations are the key ingredient for effective targeted instruction selection in LLMs.
