mlsanityData to 7 Oct 2026

Instruction Tuning with GPT-4

arXiv 2304.03277 ↗First posted 6 Apr 2023cs.CL cs.AIcited by 676

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Cited by 94 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Prior work has shown that finetuning large language models (LLMs) using machine-generated instruction-following data enables such models to achieve remarkable zero-shot capabilities on new tasks, and no human-written instructions are needed. In this paper, we present the first attempt to use GPT-4 to generate instruction-following data for LLM finetuning. Our early experiments on instruction-tuned LLaMA models show that the 52K English and Chinese instruction-following data generated by GPT-4 leads to superior zero-shot performance on new tasks to the instruction-following data generated by previous state-of-the-art models. We also collect feedback and comparison data from GPT-4 to enable a comprehensive evaluation and reward model training. We make our data generated using GPT-4 as well as our codebase publicly available.

Key facts. Cited by 676 papers in the map (data through 7 Oct 2026). Builds on 21 of its 27 references that are in the map. First posted on arXiv 6 Apr 2023.

Builds on

21 of 27 references.

References · 21

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2022Training language models to follow instructions with human feedbackcited by 15,712
  3. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  4. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  5. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,747
  6. 2022OPT: Open Pre-trained Transformer Language Modelscited by 3,464
  7. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,317
  8. 2022Scaling Instruction-Finetuned Language Modelscited by 2,997
  9. 2022Constitutional AI: Harmlessness from AI Feedbackcited by 2,950
  10. 2022Self-Instruct: Aligning Language Models with Self-Generated Instructionscited by 2,674
  11. 2022BLOOM: A 176B-Parameter Open-Access Multilingual Language Modelcited by 1,968
  12. 2021Multitask Prompted Training Enables Zero-Shot Task Generalizationcited by 1,462
9 more
  1. 2021A General Language Assistant as a Laboratory for Alignmentcited by 1,023
  2. 2023LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attentioncited by 776
  3. 2022Unnatural Instructions: Tuning Language Models with (Almost) No Human Laborcited by 395
  4. 2023Language Models can Solve Computer Taskscited by 371
  5. 2023Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedbackcited by 351
  6. 2022PromptSource: An Integrated Development Environment and Repository for Natural Language Promptscited by 288
  7. 2022OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalizationcited by 235
  8. 2022UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Modelscited by 231
  9. 2021Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collectionscited by 128

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 225; 2024: 237; 2025: 148; 2026: 66.

676 papers.

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  1. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
  2. 2023Visual Instruction Tuningcited by 7,792
  3. 2023QLoRA: Efficient Finetuning of Quantized LLMscited by 3,355
  4. 2023LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Daycited by 1,287
  5. 2023MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilitiescited by 1,221
  6. 2023Instruction-Following Evaluation for Large Language Modelscited by 1,143
  7. 2023Large Language Models are not Fair Evaluatorscited by 1,050
  8. 2023A Survey on Multimodal Large Language Modelscited by 898
  9. 2024DoRA: Weight-Decomposed Low-Rank Adaptationcited by 740
  10. 2023AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedbackcited by 738
  11. 2023OpenAssistant Conversations -- Democratizing Large Language Model Alignmentcited by 712
  12. 2023Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Modelscited by 695
38 more
  1. 2023A Comprehensive Overview of Large Language Modelscited by 639
  2. 2023LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Modelcited by 602
  3. 2023HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Modelscited by 572
  4. 2024DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understandingcited by 559
  5. 2023Prometheus: Inducing Fine-grained Evaluation Capability in Language Modelscited by 558
  6. 2023Otter: A Multi-Modal Model with In-Context Instruction Tuningcited by 548
  7. 2024GPT-4V(ision) is a Generalist Web Agent, if Groundedcited by 547
  8. 2023SALMONN: Towards Generic Hearing Abilities for Large Language Modelscited by 492
  9. 2023MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuningcited by 483
  10. 2023OCRBench: On the Hidden Mystery of OCR in Large Multimodal Modelscited by 466
  11. 2023DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Modelcited by 455
  12. 2023Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuningcited by 439
  13. 2023How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resourcescited by 405
  14. 2023Understanding the Effects of RLHF on LLM Generalisation and Diversitycited by 386
  15. 2024Hallucination of Multimodal Large Language Models: A Surveycited by 380
  16. 2024SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inferencecited by 378
  17. 2023SpecInfer: Accelerating Generative Large Language Model Serving with Tree-based Speculative Inference and Verificationcited by 359
  18. 2023An Embodied Generalist Agent in 3D Worldcited by 355
  19. 2023Chameleon: Plug-and-Play Compositional Reasoning with Large Language Modelscited by 352
  20. 2023JudgeLM: Fine-tuned Large Language Models are Scalable Judgescited by 351
  21. 2023Vision-Language Foundation Models as Effective Robot Imitatorscited by 344
  22. 2023Large Language Models for Information Retrieval: A Surveycited by 331
  23. 2023PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimizationcited by 311
  24. 2023Unified-IO 2: Scaling Autoregressive Multimodal Models with Vision, Language, Audio, and Actioncited by 301
  25. 2023Evaluating Large Language Models at Evaluating Instruction Followingcited by 290
  26. 2023Preference Ranking Optimization for Human Alignmentcited by 283
  27. 2023SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Modelscited by 283
  28. 2023ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solvingcited by 276
  29. 2024A Survey on Knowledge Distillation of Large Language Modelscited by 276
  30. 2023Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Mergingcited by 271
  31. 2024RLHF Workflow: From Reward Modeling to Online RLHFcited by 265
  32. 2023MIMIC-IT: Multi-Modal In-Context Instruction Tuningcited by 264
  33. 2023Sentiment Analysis in the Era of Large Language Models: A Reality Checkcited by 262
  34. 2024Is DPO Superior to PPO for LLM Alignment? A Comprehensive Studycited by 262
  35. 2023MultiModal-GPT: A Vision and Language Model for Dialogue with Humanscited by 255
  36. 2023The False Promise of Imitating Proprietary LLMscited by 254
  37. 2023OpenChat: Advancing Open-source Language Models with Mixed-Quality Datacited by 250
  38. 2023Multimodal Foundation Models: From Specialists to General-Purpose Assistantscited by 247

50 most cited of 676 All 676 (JSON)

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  1. 2024Non-instructional Fine-tuning: Enabling Instruction-Following Capabilities in Pre-trained Language Models without Instruction-Following Data
  2. 2024Rapidly Developing High-quality Instruction Data and Evaluation Benchmark for Large Language Models with Minimal Human Effort: A Case Study on Japanese
  3. 2024Enhancing and Assessing Instruction-Following with Fine-Grained Instruction Variants
  4. 2023Tuna: Instruction Tuning using Feedback from Large Language Models
  5. 2023Dynamics of Instruction Fine-Tuning for Chinese Large Language Models
  6. 2023WizardLM: Empowering large pre-trained language models to follow complex instructions
  7. 2024Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
  8. 2026GIFT: Guided Fine-Tuning and Transfer for Enhancing Instruction-Tuned Language Models