Papers by Ruien Jiang

1 papers
BLADE: Benchmarking Language Model Agents for Data-Driven Science (2024.findings-emnlp)

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Challenge: Language model-based agents can be used to conduct and support data-driven science, but evaluating them on open-ended tasks is challenging due to multiple valid approaches, partially correct steps, and different ways to express the same decisions.
Approach: They propose a benchmark to automatically evaluate agents’ multifaceted approaches to open-ended research questions.
Outcome: BLADE evaluates agents’ multifaceted approaches to open-ended research questions using data from 12 datasets and research questions drawn from existing scientific literature.

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