3 papers
cs.HC2026
AI Persona, Service Consumption, and User Intent Entropy: Field Experimental Evidence from an LLM Platform
Junjie Li, Xiaofan Li, Lauren Xiaoyuan Lu +2
Problem definition: Firms deploying large language model services must decide how their AI communicates, not just what it can do. We examine how a relational persona - warmer, more…
cs.CL2025
DSPO: Stable and Efficient Policy Optimization for Agentic Search and Reasoning
Chenyang Gu, Yewen Pu, Bruce Yang +2
Enhancing LLMs with the ability to actively search external knowledge is crucial for complex and real-world tasks. Current approaches either rely on prompting to elicit the model's…
cs.AI2025
CodeAgents: A Token-Efficient Framework for Codified Multi-Agent Reasoning in LLMs
Bruce Yang, Xinfeng He, Huan Gao +3
Effective prompt design is essential for improving the planning capabilities of large language model (LLM)-driven agents. However, existing structured prompting strategies are typi…