mlsanityData to 7 Oct 2026

LAB: Large-Scale Alignment for ChatBots

arXiv 2403.01081 ↗First posted 2 Mar 2024cs.CL cs.LGcited by 39

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Abstract (arXiv)

This work introduces LAB (Large-scale Alignment for chatBots), a novel methodology designed to overcome the scalability challenges in the instruction-tuning phase of large language model (LLM) training. Leveraging a taxonomy-guided synthetic data generation process and a multi-phase tuning framework, LAB significantly reduces reliance on expensive human annotations and proprietary models like GPT-4. We demonstrate that LAB-trained models can achieve competitive performance across several benchmarks compared to models trained with traditional human-annotated or GPT-4 generated synthetic data. Thus offering a scalable, cost-effective solution for enhancing LLM capabilities and instruction-following behaviors without the drawbacks of catastrophic forgetting, marking a step forward in the efficient training of LLMs for a wide range of applications.

Key facts. Cited by 39 papers in the map (data through 7 Oct 2026). Builds on 16 of its 22 references that are in the map. First posted on arXiv 2 Mar 2024.

Builds on

16 of 22 references.

References · 16

  1. 2022Training language models to follow instructions with human feedbackcited by 15,712
  2. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  3. 2021Training Verifiers to Solve Math Word Problemscited by 9,743
  4. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
  5. 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 7,916
  6. 2020Measuring Massive Multitask Language Understandingcited by 7,768
  7. 2018Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challengecited by 4,710
  8. 2019HellaSwag: Can a Machine Really Finish Your Sentence?cited by 4,018
  9. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,747
  10. 2022Self-Instruct: Aligning Language Models with Self-Generated Instructionscited by 2,674
  11. 2023WizardLM: Empowering large pre-trained language models to follow complex instructionscited by 1,116
  12. 2023Zephyr: Direct Distillation of LM Alignmentcited by 498
4 more
  1. 2023MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuningcited by 483
  2. 2023The False Promise of Imitating Proprietary LLMscited by 254
  3. 2018Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflowcited by 165
  4. 2023Orca 2: Teaching Small Language Models How to Reasoncited by 157

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 19; 2025: 14; 2026: 6.

39 papers.

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  1. 2024On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Surveycited by 240
  2. 2024Programming Refusal with Conditional Activation Steeringcited by 191
  3. 2024SEAL: Safety-enhanced Aligned LLM Fine-tuning via Bilevel Data Selectioncited by 64
  4. 2024Granite-Function Calling Model: Introducing Function Calling Abilities via Multi-task Learning of Granular Taskscited by 52
  5. 2024A Survey on Data Synthesis and Augmentation for Large Language Modelscited by 40
  6. 2024Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMscited by 39
  7. 2024Queue management for slo-oriented large language model servingcited by 36
  8. 2026On Data Engineering for Scaling LLM Terminal Capabilitiescited by 34
  9. 2024DesignQA: A Multimodal Benchmark for Evaluating Large Language Models' Understanding of Engineering Documentationcited by 30
  10. 2024Towards AI-Native Software Engineering (SE 3.0): A Vision and a Challenge Roadmapcited by 30
  11. 2024Docling Technical Reportcited by 29
  12. 2025Large Language Models Meet Symbolic Provers for Logical Reasoning Evaluationcited by 27
27 more
  1. 2024Holmes: A Benchmark to Assess the Linguistic Competence of Language Modelscited by 26
  2. 2024Distributional Preference Alignment of LLMs via Optimal Transportcited by 26
  3. 2024Self-MoE: Towards Compositional Large Language Models with Self-Specialized Expertscited by 22
  4. 2024Naturally Occurring Feedback is Common, Extractable and Usefulcited by 14
  5. 2024textitTrans-LoRA: towards data-free Transferable Parameter Efficient Finetuningcited by 13
  6. 2025Systematic Knowledge Injection into Large Language Models via Diverse Augmentation for Domain-Specific RAGcited by 9
  7. 2025Knowledge Base Construction for Knowledge-Augmented Text-to-SQLcited by 9
  8. 2024Multi-Document Grounded Multi-Turn Synthetic Dialog Generationcited by 7
  9. 2025Middo: Model-Informed Dynamic Data Optimization for Enhanced LLM Fine-Tuning via Closed-Loop Learningcited by 7
  10. 2025A Survey of LLM × DATAcited by 4
  11. 2025Scopes of Alignmentcited by 3
  12. 2025Establishing a Scale for Kullback-Leibler Divergence in Language Models Across Various Settingscited by 3
  13. 2025Localizing Persona Representations in LLMscited by 3
  14. 2025OneShield -- the Next Generation of LLM Guardrailscited by 3
  15. 2024OnlySportsLM: Optimizing Sports-Domain Language Models with SOTA Performance under Billion Parameterscited by 2
  16. 2024Retrieval Augmented Generation-Based Incident Resolution Recommendation System for IT Supportcited by 2
  17. 2024Reducing the Scope of Language Modelscited by 1
  18. 2025Feedback-Driven Vision-Language Alignment with Minimal Human Supervisioncited by 1
  19. 2025We Need Improved Data Curation and Attribution in AI for Scientific Discoverycited by 1
  20. 2025Fine-Tuned Thoughts: Leveraging Chain-of-Thought Reasoning for Industrial Asset Health Monitoringcited by 1
  21. 2026AcquisitionSynthesis: Targeted Data Generation using Acquisition Functionscited by 1
  22. 2026Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RLcited by 1
  23. 2025Backprompting: Leveraging Synthetic Production Data for Health Advice Guardrailscited by 0
  24. 2025Exploring Human Perceptions of AI Responses: Insights from a Mixed-Methods Study on Risk Mitigation in Generative Modelscited by 0
  25. 2026Efficient Embedding-based Synthetic Data Generation for Complex Reasoning Taskscited by 0
  26. 2026StoicLLM: Preference Optimization for Philosophical Alignment in Small Language Modelscited by 0
  27. 2026EmbGen: Teaching with Reassembled Corporacited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges
  2. 2025Aligning Large Language Models via Fully Self-Synthetic Data
  3. 2023Aligning Large Language Models through Synthetic Feedback
  4. 2023Align on the Fly: Adapting Chatbot Behavior to Established Norms
  5. 2023Large Language Model Alignment: A Survey
  6. 2023Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision
  7. 2023Chat Vector: A Simple Approach to Equip LLMs with Instruction Following and Model Alignment in New Languages
  8. 2024Impact of Decoding Methods on Human Alignment of Conversational LLMs