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This paper describes IDA-Bench, a new benchmark for evaluating Large Language Models (LLMs) as interactive data analysis agents. Unlike existing benchmarks that focus on single-turn interactions, IDA-Bench assesses LLMs in multi-round dialogues with a simulated user, mirroring the iterative and subjective nature of real-world data analysis. Tasks are derived from complex Kaggle notebooks and presented as sequential natural language instructi

IDA-Bench: Evaluating LLMs on Interactive Guided Data Analysis

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