Data Interpreter
Object
Data Interpreter is an advanced LLM-based agent designed to solve complex data science problems end-to-end. It addresses the challenges of handling interconnected tasks, dynamic data adjustments, and domain-specific expertise requirements that traditional approaches struggle with. The system employs sophisticated hierarchical modeling to break down complex problems into manageable components while maintaining adaptability to real-time changes.
Features
- Hierarchical Graph Modeling: Decomposes complex problems into subproblems, enabling dynamic node generation and graph optimization for adaptive workflow management
- Programmable Node Generation: Refines and verifies each subproblem iteratively to improve code generation results and enhance robustness
- Real-time data adaptability through dynamic planning with hierarchical structures
- Logical inconsistency identification and experience recording for continuous improvement
Outcome
Data Interpreter demonstrates superior performance across various benchmarks, achieving a 25% accuracy improvement on InfiAgent-DABench (from 75.9% to 94.9%), enhancing machine learning task performance from 88% to 95%, and showing a remarkable 26% improvement on the MATH dataset compared to state-of-the-art baselines. The system excels particularly in open-ended tasks with a 112% performance boost, making it an exceptional tool for comprehensive data science workflows.