ODYSSE: A New Framework for Personalized Agentic Reasoning
Researchers have introduced ODYSSE, a Reinforced Fine-Tuning (RFT) framework designed to address personalized agentic reasoning—a challenge where AI agents must interpret ambiguous user requests and interact with environments to deliver tailored services. The framework's core innovation is Episode-wise GRPO (ESPO), an extension of Group Relative Policy Optimization (GRPO) that handles long action horizons and strong cross-step dependencies. This work, detailed in a preprint on arXiv (2607.25369), targets human-centered scenarios where instructions are not well-defined, requiring agents to decode personal preferences to narrow open-ended solution spaces. The approach aims to advance agentic systems' ability to provide personalized services in real-world contexts.
Key facts
- ODYSSE is a Reinforced Fine-Tuning (RFT) framework for personalized agentic reasoning.
- It introduces Episode-wise GRPO (ESPO), an extension of Group Relative Policy Optimization (GRPO).
- ESPO addresses long action horizons and strong cross-step dependencies.
- The framework targets human-centered scenarios with ambiguous user requests.
- It requires agents to jointly interact with users and environments.
- The goal is to decode personalized preferences to narrow solution spaces.
- The paper is available on arXiv with ID 2607.25369.
- The work focuses on advancing agentic systems for personalized services.
Entities
Institutions
- arXiv