CDR-Bench: Evaluating Faithful Execution of Compositional, Order-Sensitive Data Refinement Recipes
arXiv:2606.31435v1 Announce Type: cross Abstract: Data refinement involves executing multi-step recipes over evolving text states, where both composition and execution order of processing operators determine the outcome. While existing benchmarks either isolate text editing or entangle it with code and tool execution, it remains unclear whether LLMs can directly and faithfully execute these compositional, order-sensitive data refinement recipes. To fill this gap, we introduce CDR-Bench, a comprehensive benchmark featuring 3,462 high-quality tasks spanning four real-world data refinement domain
The rapid advancement and adoption of large language models are creating a critical need for robust evaluation benchmarks that specifically address complex, multi-step data processing. This paper addresses a current gap in evaluating LLM capabilities for compositional and order-sensitive tasks.
A strategic reader should care because improving LLM's ability to faithfully execute complex data refinement tasks is crucial for their integration into higher-value, autonomous workflows, directly impacting productivity and the utility of AI agents.
The introduction of CDR-Bench provides a standardized method to evaluate and drive improvements in LLM's compositional reasoning and meticulous execution of instructions, thereby accelerating the development of more reliable and versatile AI systems.
- · AI developers
- · Data scientists
- · SaaS providers leveraging AI
- · Businesses adopting AI for workflow automation
- · Companies with inefficient data processing workflows
- · Legacy automated data refinement tools
The benchmark will allow for clearer comparison and accelerated development of LLMs for complex data manipulation tasks.
Improved LLM performance on these tasks will lead to faster adoption of AI agents in roles requiring multi-step data refinement, automating more white-collar workflows.
As AI agents become more adept at complex data tasks, the demand for human oversight shifts from execution to strategic formulation, leading to a restructuring of knowledge work.
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Read at arXiv cs.CL