mlsanityData to 7 Oct 2026

PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context Learning

arXiv 2405.02501 ↗First posted 3 May 2024cs.CL cs.AIcited by 28

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Abstract (arXiv)

Large Language Models (LLMs) are trained on massive text corpora, which are encoded with diverse personality traits. This triggers an interesting goal of eliciting a desired personality trait from the LLM, and probing its behavioral preferences. Accordingly, we formalize the persona elicitation task, aiming to customize LLM behaviors to align with a target persona. We present Persona In-Context Learning (PICLe), a novel persona elicitation framework grounded in Bayesian inference. At the core, PICLe introduces a new ICL example selection criterion based on likelihood ratio, which is designed to optimally guide the model in eliciting a specific target persona. We demonstrate the effectiveness of PICLe through extensive comparisons against baseline methods across three contemporary LLMs. Code is available at https://github.com/deeplearning-wisc/picle.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). Builds on 39 of its 48 references that are in the map. First posted on arXiv 3 May 2024.

Builds on

39 of 48 references.

References · 39

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2022Training language models to follow instructions with human feedbackcited by 15,712
  3. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  4. 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 7,916
  5. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,747
  6. 2022Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackcited by 3,634
  7. 2022OPT: Open Pre-trained Transformer Language Modelscited by 3,464
  8. 2022Scaling Instruction-Finetuned Language Modelscited by 2,997
  9. 2022Constitutional AI: Harmlessness from AI Feedbackcited by 2,950
  10. 2023Universal and Transferable Adversarial Attacks on Aligned Language Modelscited by 2,914
  11. 2022Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?cited by 1,413
  12. 2021What Makes Good In-Context Examples for GPT-3?cited by 1,184
27 more
  1. 2021An Explanation of In-context Learning as Implicit Bayesian Inferencecited by 915
  2. 2022Discovering Language Model Behaviors with Model-Written Evaluationscited by 805
  3. 2021Learning To Retrieve Prompts for In-Context Learningcited by 641
  4. 2022Improving alignment of dialogue agents via targeted human judgementscited by 527
  5. 2023"Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Modelscited by 457
  6. 2021MetaICL: Learning to Learn In Contextcited by 450
  7. 2022Memory-Based Model Editing at Scalecited by 443
  8. 2022Teaching language models to support answers with verified quotescited by 290
  9. 2023Shadow Alignment: The Ease of Subverting Safely-Aligned Language Modelscited by 284
  10. 2023The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learningcited by 251
  11. 2023Pretraining Language Models with Human Preferencescited by 245
  12. 2022Selective Annotation Makes Language Models Better Few-Shot Learnerscited by 242
  13. 2023Evaluating the Moral Beliefs Encoded in LLMscited by 211
  14. 2023Marked Personas: Using Natural Language Prompts to Measure Stereotypes in Language Modelscited by 204
  15. 2023Personality Traits in Large Language Modelscited by 166
  16. 2023In-Context Impersonation Reveals Large Language Models' Strengths and Biasescited by 154
  17. 2023Fundamental Limitations of Alignment in Large Language Modelscited by 152
  18. 2023Unified Demonstration Retriever for In-Context Learningcited by 141
  19. 2022Evaluating and Inducing Personality in Pre-trained Language Modelscited by 122
  20. 2020Adversarial Training for Large Neural Language Modelscited by 109
  21. 2022Self-Generated In-Context Learning: Leveraging Auto-regressive Language Models as a Demonstration Generatorcited by 68
  22. 2023Language Instructed Reinforcement Learning for Human-AI Coordinationcited by 61
  23. 2023Do LLMs Possess a Personality? Making the MBTI Test an Amazing Evaluation for Large Language Modelscited by 54
  24. 2023Small Models are Valuable Plug-ins for Large Language Modelscited by 42
  25. 2023Direct Preference-based Policy Optimization without Reward Modelingcited by 36
  26. 2023Which Examples to Annotate for In-Context Learning? Towards Effective and Efficient Selectioncited by 36
  27. 2022Prompt Injection: Parameterization of Fixed Inputscited by 35

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 8; 2025: 15; 2026: 5.

28 papers.

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  1. 2024Scaling Synthetic Data Creation with 1,000,000,000 Personascited by 397
  2. 2024Process Reward Model with Q-Value Rankingscited by 78
  3. 2024Safety-Aware Fine-Tuning of Large Language Modelscited by 33
  4. 2025Whose Personae? Synthetic Persona Experiments in LLM Research and Pathways to Transparencycited by 14
  5. 2024Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superpositioncited by 13
  6. 2024Self-assessment, Exhibition, and Recognition: a Review of Personality in Large Language Modelscited by 10
  7. 2024Revealing and Mitigating the Challenge of Detecting Character Knowledge Errors in LLM Role-Playingcited by 9
  8. 2025The Power of Personality: A Human Simulation Perspective to Investigate Large Language Model Agentscited by 8
  9. 2024Challenges and Future Directions of Data-Centric AI Alignmentcited by 5
  10. 2025From Five Dimensions to Many: Large Language Models as Precise and Interpretable Psychological Profilerscited by 5
  11. 2024BTBR: A Bayesian-Theory-Driven Probabilistic-Fuzzy Framework for Implicit Bias Removal in Large Language Modelscited by 4
  12. 2025Spatial Audio Processing with Large Language Model on Wearable Devicescited by 4
16 more
  1. 2025AdAEM: An Adaptively and Automated Extensible Measurement of LLMs' Value Differencecited by 4
  2. 2025RIDE: Enhancing Large Language Model Alignment through Restyled In-Context Learning Demonstration Exemplarscited by 2
  3. 2025Generating Synthetic Oracle Datasets to Analyze Noise Impact: A Study on Building Function Classification Using Tweetscited by 2
  4. 2025PICACO: Pluralistic In-Context Value Alignment of LLMs via Total Correlation Optimizationcited by 2
  5. 2025Hateful Person or Hateful Model? Investigating the Role of Personas in Hate Speech Detection by Large Language Modelscited by 1
  6. 2025Synthia: Scalable Grounded Persona Generation from Social Media Datacited by 1
  7. 2025IROTE: Human-like Traits Elicitation of Large Language Model via In-Context Self-Reflective Optimizationcited by 1
  8. 2025Phi: Preference Hijacking in Multi-modal Large Language Models at Inference Timecited by 1
  9. 2025A Multi-Labeled Dataset for Indonesian Discourse: Examining Toxicity, Polarization, and Demographics Informationcited by 0
  10. 2025Batch Aggregation: An Approach to Enhance Text Classification with Correlated Augmented Datacited by 0
  11. 2025SOLAR: Towards Characterizing Subjectivity of Individuals through Modeling Value Conflicts and Trade-offscited by 0
  12. 2026Operating Within the Operational Design Domain: Zero-Shot Perception with Vision-Language Modelscited by 0
  13. 2026What Do Safety-Aligned LLMs Learn From Mixed Compliance Demonstrations?cited by 0
  14. 2026SupplyNet: Supporting Visual Exploratory Learning in Supply Chain via Contextual Multi-Agent Simulationcited by 0
  15. 2026Implicit Personality Representations in Humans and LLMscited by 0
  16. 2026Echoes of Deeds: Moral History Can Shape and Steer LLM Behavioral Choicescited by 0