Workflow-R1: Group Sub-sequence Policy Optimization for Multi-turn Workflow Construction

TL;DR

Workflow-R1 introduces a multi-turn, natural language-based framework for workflow construction, utilizing a novel Group Sub-sequence Policy Optimization method to improve multi-turn reasoning in agentic workflows.

Contribution

It reformulates workflow synthesis as a sequential decision-making process and proposes GSsPO, a structure-aware RL algorithm tailored for multi-turn agentic reasoning tasks.

Findings

Outperforms baseline methods on multiple QA benchmarks

Validates GSsPO as a general solution for sequential reasoning

Establishes Workflow-R1 as a new paradigm for workflow optimization

Abstract

The rapid evolution of agentic workflows has demonstrated strong performance of LLM-based agents in addressing complex reasoning tasks. However, existing workflow optimization methods typically formulate workflow synthesis as a static, one-shot code-centric generation problem. This paradigm imposes excessive constraints on the model's coding capabilities and restricts the flexibility required for dynamic problem-solving. In this paper, we present Workflow-R1, a framework that reformulates workflow construction as a multi-turn, natural language-based sequential decision-making process. To resolve the optimization granularity mismatch inherent in such multi-turn interactions, we introduce Group Sub-sequence Policy Optimization (GSsPO). While explicitly tailored to align with the interleaved Think-Action dynamics of agentic reasoning, GSsPO fundamentally functions as a structure-aware RL algorithm generalizable to a broad class of multi-turn agentic sequential decision-making tasks. By recalibrating the optimization unit to the composite sub-sequence, specifically the atomic Think-Action cycle, it aligns gradient updates with the semantic boundaries of these interactions, ensuring robust learning in complex multi-turn reasoning tasks. Through extensive experiments on multiple QA benchmarks, Workflow-R1 outperforms competitive baselines, validating GSsPO as a generalized solution for sequential reasoning and establishing Workflow-R1 as a promising new paradigm for automated workflow optimization.