mlsanityData to 14 Oct 2026

Into the Unknown: Self-Learning Large Language Models

arXiv 2402.09147 ↗First posted 14 Feb 2024cs.AIcited by 5

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Abstract (arXiv)

We address the main problem of self-learning LLM: the question of what to learn. We propose a self-learning LLM framework that enables an LLM to independently learn previously unknown knowledge through self-assessment of their own hallucinations. We introduce a concept called Point in the Unknown (PiU) to identify atomic knowledge unknown to a model, along with four methods for automatic PiUs identification, facilitating the creation of a self-learning loop that focuses exclusively on the absorption of currently unknown knowledge into the model. Additionally, we developed evaluation metrics to gauge an LLM's self-learning capability. Our experiments revealed that LLMs with at least 3B parameters that have undergone some instruction training would be able to perform self-learning well. We further proved the effectiveness of self-learning by comparing the performance of a model that has undergone self-learning to a model that has not. Our self-learning concept allows more efficient LLM updates and opens new perspectives for LLM knowledge exchange.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 34 of its 63 references that are in the map. First posted on arXiv 14 Feb 2024.

Builds on

34 of 63 references.

References · 34

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  3. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  4. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  5. 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 8,065
  6. 2016Overcoming catastrophic forgetting in neural networkscited by 4,787
  7. 2023Mistral 7Bcited by 3,164
  8. 2021TruthfulQA: Measuring How Models Mimic Human Falsehoodscited by 2,975
  9. 2023Inference-Time Intervention: Eliciting Truthful Answers from a Language Modelcited by 1,302
  10. 2023FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generationcited by 1,282
  11. 2023SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Modelscited by 810
  12. 2021Deduplicating Training Data Makes Language Models Bettercited by 714
22 more
  1. 2023The Internal State of an LLM Knows When It's Lyingcited by 659
  2. 2024TinyLlama: An Open-Source Small Language Modelcited by 618
  3. 2022Large Language Models Struggle to Learn Long-Tail Knowledgecited by 458
  4. 2022Memory-Based Model Editing at Scalecited by 447
  5. 2023DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Modelscited by 376
  6. 2023Do Large Language Models Know What They Don't Know?cited by 243
  7. 2020Modifying Memories in Transformer Modelscited by 224
  8. 2023Fine-tuning Language Models for Factualitycited by 221
  9. 2023Inverse Scaling: When Bigger Isn't Bettercited by 207
  10. 2023ChatGPT: Jack of all trades, master of nonecited by 204
  11. 2023Continual Pre-training of Language Modelscited by 198
  12. 2021Towards Continual Knowledge Learning of Language Modelscited by 174
  13. 2020Editable Neural Networkscited by 155
  14. 2021Lifelong Pretraining: Continually Adapting Language Models to Emerging Corporacited by 115
  15. 2021Achieving Forgetting Prevention and Knowledge Transfer in Continual Learningcited by 91
  16. 2022Entity Cloze By Date: What LMs Know About Unseen Entitiescited by 55
  17. 2022RHO (ρ): Reducing Hallucination in Open-domain Dialogues with Knowledge Groundingcited by 47
  18. 2024Learning to Trust Your Feelings: Leveraging Self-awareness in LLMs for Hallucination Mitigationcited by 44
  19. 2023Zero-Resource Hallucination Prevention for Large Language Modelscited by 19
  20. 2023AutoHall: Automated Factuality Hallucination Dataset Generation for Large Language Modelscited by 10
  21. 2023Modeling Uncertainty in Personalized Emotion Prediction with Normalizing Flowscited by 5
  22. 2023Deep Emotions Across Languages: A Novel Approach for Sentiment Propagation in Multilingual WordNetscited by 4

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 4; 2026: 1.

5 papers.

  1. 2025Visual Large Language Models for Generalized and Specialized Applicationscited by 36
  2. 2025A Survey on Enhancing Causal Reasoning Ability of Large Language Modelscited by 8
  3. 2025AggTruth: Contextual Hallucination Detection using Aggregated Attention Scores in LLMscited by 2
  4. 2025SLearnLLM: A Self-Learning Framework for Efficient Domain-Specific Adaptation of Large Language Modelscited by 0
  5. 2026Augmenting Question Answering with A Hybrid RAG Approachcited by 0