Toward Personalized LLM-Powered Agents: Foundations, Evaluation, and Future Directions
Toward Personalized LLM-Powered Agents: Foundations, Evaluation, and Future Directions explores Develop a structured framework for designing personalized LLM-powered agents to enhance user interaction and adaptability.. Commercial viability score: 4/10 in Agents.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $10K - $14K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisAgentic AI in Healthcare & Medicine: A Seven-Dimensional Taxonomy for Empirical Evaluation of LLM-based AgentsViability: 3.0
- Prior WorkThe Necessity of a Unified Framework for LLM-Based Agent EvaluationViability: 4.0
- Higher ViabilityTowards Realistic Personalization: Evaluating Long-Horizon Preference Following in Personalized User-LLM InteractionsViability: 5.0
- Higher ViabilityMemory for Autonomous LLM Agents:Mechanisms, Evaluation, and Emerging FrontiersViability: 7.0
- Higher ViabilityLearning Personalized Agents from Human Feedback
Related Resources
- AgentSpeak(glossary)
- Mixture-of-Agents(glossary)
- Agents(glossary)
- What is the future of AI agents according to Nothing's CEO?(question)
- How do LLM efficiency advancements impact the development of AI agents?(question)
- How does AgentXRay contribute to the explainability of AI agents in complex decision-making processes?(question)
- Agents – Use Cases(use_case)