PersMem: Internalizing Personality into Dual-Pathway Memory for LLM Agents
cs.AI
Submitted: 2026-09-28
Updated: 2026-09-28
Sources
- From Persona to Personalization: A Survey on Role-Playing Language Agents
- Persona Vectors: Monitoring and Controlling Character Traits in Language Models
- Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory
- ContextEcho: A Benchmark for Persona Drift in Long Agentic-Coding Sessions
- The Personality Illusion: Revealing Dissociation Between Self-Reports & Behavior in LLMs
- AI-Associated Lexical Shifts Across 34 Languages: Cross-Lingual Convergence and Diachronic Uptake in News Writing
- NRC VAD Lexicon v2: Norms for Valence, Arousal, and Dominance for over 55k English Terms
- Personality Traits in Large Language Models
- Human Psychometric Questionnaires Mischaracterize LLM Behavior
- Staying In Character: Perspective-Bounded Memory For Book-Based Role-Playing Agents
- Beyond Preset Identities: Selective Stance Accommodation and Interaction Reorganisation in Generative Agent Societies
- Representation Engineering: A Top-Down Approach to AI Transparency
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- Agents' Last Exam
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems