mlsanityData to 7 Oct 2026

Failures Pave the Way: Enhancing Large Language Models through Tuning-free Rule Accumulation

arXiv 2310.15746 ↗First posted 24 Oct 2023cs.CLcited by 30

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Abstract (arXiv)

Large Language Models (LLMs) have showcased impressive performance. However, due to their inability to capture relationships among samples, these frozen LLMs inevitably keep repeating similar mistakes. In this work, we propose our Tuning-free Rule Accumulation (TRAN) framework, which guides LLMs in improving their performance by learning from previous mistakes. Considering data arrives sequentially, LLMs gradually accumulate rules from incorrect cases, forming a rule collection. These rules are then utilized by the LLMs to avoid making similar mistakes when processing subsequent inputs. Moreover, the rules remain independent of the primary prompts, seamlessly complementing prompt design strategies. Experimentally, we show that TRAN improves over recent baselines by a large margin.

Key facts. Cited by 30 papers in the map (data through 7 Oct 2026). Builds on 33 of its 52 references that are in the map. First posted on arXiv 24 Oct 2023.

Builds on

33 of 52 references.

References · 33

  1. 2022Training language models to follow instructions with human feedbackcited by 15,712
  2. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  3. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  4. 2022Large Language Models are Zero-Shot Reasonerscited by 4,323
  5. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,064
  6. 2017Deep reinforcement learning from human preferencescited by 3,846
  7. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,317
  8. 2022Self-Instruct: Aligning Language Models with Self-Generated Instructionscited by 2,674
  9. 2015Character-level Convolutional Networks for Text Classificationcited by 2,293
  10. 2022Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelscited by 1,970
  11. 2022Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Themcited by 1,767
  12. 2023LIMA: Less Is More for Alignmentcited by 1,080
21 more
  1. 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivitycited by 888
  2. 2022Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learningcited by 886
  3. 2023Automatic Prompt Optimization with "Gradient Descent" and Beam Searchcited by 628
  4. 2023Instruction Tuning for Large Language Models: A Surveycited by 617
  5. 2019Gradient based sample selection for online continual learningcited by 568
  6. 2022Improving alignment of dialogue agents via targeted human judgementscited by 527
  7. 2020TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classificationcited by 414
  8. 2021Learning How to Ask: Querying LMs with Mixtures of Soft Promptscited by 376
  9. 2023Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervisioncited by 318
  10. 2023Exploring Large Language Models for Communication Games: An Empirical Study on Werewolfcited by 238
  11. 2022Re3: Generating Longer Stories With Recursive Reprompting and Revisioncited by 193
  12. 2019Meta-Learning Representations for Continual Learningcited by 189
  13. 2023WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human Preferencescited by 100
  14. 2022Continual Learning of Natural Language Processing Tasks: A Surveycited by 83
  15. 2020Learning from Task Descriptionscited by 78
  16. 2020How Can Self-Attention Networks Recognize Dyck-n Languages?cited by 51
  17. 2023Reprompting: Automated Chain-of-Thought Prompt Inference Through Gibbs Samplingcited by 46
  18. 2021Dual-Teacher Class-Incremental Learning With Data-Free Generative Replaycited by 31
  19. 2022Balancing Stability and Plasticity through Advanced Null Space in Continual Learningcited by 29
  20. 2023Learn to Memorize: Scalable Continual Learning in Semiparametric Models with Mixture-of-Neighbors Induction Memorycited by 12
  21. 2023Restricted Orthogonal Gradient Projection for Continual Learningcited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 15; 2025: 10; 2026: 5.

30 papers.

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  1. 2024A Survey on Self-Evolution of Large Language Modelscited by 86
  2. 2025Self-Evolving Multi-Agent Simulations for Realistic Clinical Interactionscited by 40
  3. 2024WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agentscited by 24
  4. 2024Beyond Instruction Following: Evaluating Inferential Rule Following of Large Language Modelscited by 23
  5. 2024IDEA: Enhancing the Rule Learning Ability of Large Language Model Agent through Induction, Deduction, and Abductioncited by 20
  6. 2024SoFA: Shielded On-the-fly Alignment via Priority Rule Followingcited by 18
  7. 2024Driving Style Alignment for LLM-powered Driver Agentcited by 15
  8. 2025Truly Self-Improving Agents Require Intrinsic Metacognitive Learningcited by 13
  9. 2026On Safety Risks in Experience-Driven Self-Evolving Agentscited by 12
  10. 2024RoT: Enhancing Large Language Models with Reflection on Search Treescited by 11
  11. 2024ItD: Large Language Models Can Teach Themselves Induction through Deductioncited by 8
  12. 2024Collaborative Evolving Strategy for Automatic Data-Centric Developmentcited by 6
18 more
  1. 2024TPD: Enhancing Student Language Model Reasoning via Principle Discovery and Guidancecited by 5
  2. 2024Towards Unified Alignment Between Agents, Humans, and Environmentcited by 5
  3. 2024AdaSwitch: Adaptive Switching between Small and Large Agents for Effective Cloud-Local Collaborative Learningcited by 5
  4. 2025WALL-E 2.0: World Alignment by NeuroSymbolic Learning improves World Model-based LLM Agentscited by 5
  5. 2026Large Language Model Agents Are Not Always Faithful Self-Evolverscited by 5
  6. 2025JRE-L: Journalist, Reader, and Editor LLMs in the Loop for Science Journalism for the General Audiencecited by 3
  7. 2025Can Past Experience Accelerate LLM Reasoning?cited by 3
  8. 2024LLM-Collaboration on Automatic Science Journalism for the General Audiencecited by 2
  9. 2024Error-driven Data-efficient Large Multimodal Model Tuningcited by 2
  10. 2025ExpeTrans: LLMs Are Experiential Transfer Learnerscited by 2
  11. 2025Learning Wisdom from Errors: Promoting LLM's Continual Relation Learning through Exploiting Error Casescited by 2
  12. 2024Concept Distillation from Strong to Weak Models via Hypotheses-to-Theories Promptingcited by 1
  13. 2026MetaEvo: A Meta-Optimization Framework for Experience-Driven Agent Evolutioncited by 1
  14. 2025PSSD: Making Large Language Models Self-denial via Human Psyche Structurecited by 0
  15. 2025CMQCIC-Bench: A Chinese Benchmark for Evaluating Large Language Models in Medical Quality Control Indicator Calculationcited by 0
  16. 2025Error-Driven Scene Editing for 3D Grounding in Large Language Modelscited by 0
  17. 2026MedEvoEval: Evaluating Continual Evolution of Doctor Agents through Simulated Clinical Episodescited by 0
  18. 2026SAGE: Self-Evolving Storyboard Skills via Attribution-Guided Rule Evolutioncited by 0