Summary
A paper on arXiv (2505.12352) by Jinxian Qu, Qingqing Gu, and Teng Chen proposes a novel value-based framework for aligning LLM-based agents with human social values. Addressing deficiencies in self-cognition, dilemma decision-making, and self-emotions, the framework uses GraphRAG to convert abstract principles into value-based instructions, retrieving the suitable instruction based on a specific conversation context to steer agent behavior as expected. To quantitatively evaluate the ratio of expected behaviors, the authors define expected behaviors from two established psychological theories: Maslow's Hierarchy of Needs and Plutchik's Wheel of Emotion. Experiments on the DAILYDILEMMAS benchmark demonstrate significant performance gains over prompt-based baselines, including ECoT, Plan-and-Solve, and metacognitive prompting. The authors state the approach lays a foundation for the emergence of self-emotions in AI systems. Published May 17, 2026, in the NLP domain.
Paper Overview
- Research Area: NLP
- Authors: Jinxian Qu, Qingqing Gu, Teng Chen
- Published: 2026-05-17
- arXiv: 2505.12352
Abstract
Wide applications of LLM-based agents require strong alignment with human social values. However, current works still exhibit deficiencies in self-cognition and dilemma decision, as well as self-emotions. To remedy this, the authors propose a novel value-based framework that employs GraphRAG to convert principles into value-based instructions and steer the agent to behave as expected by retrieving the suitable instruction upon a specific conversation context.
To evaluate the ratio of expected behaviors, they define expected behaviors from two famous theories:
- Maslow's Hierarchy of Needs
- Plutchik's Wheel of Emotion
By experimenting with the method on the benchmark of DAILYDILEMMAS, it exhibits significant performance gains compared to prompt-based baselines, including:
- ECoT
- Plan-and-Solve
- Metacognitive Prompting
The authors state the method provides a foundation for the emergence of self-emotions in AI systems.
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