mlsanityData to 7 Oct 2026

LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models

arXiv 2306.12420 ↗First posted 21 Jun 2023cs.CL cs.AIcited by 58

Not on the map. Why?

Abstract (arXiv)

Foundation models have demonstrated a great ability to achieve general human-level intelligence far beyond traditional approaches. As the technique keeps attracting attention from the AI community, an increasing number of foundation models are becoming publicly accessible. However, a significant shortcoming of most of these models lies in their performance in specialized-domain and task-specific applications, necessitating domain- and task-aware fine-tuning to develop effective scientific language models. As the number of available foundation models and specialized tasks keeps growing, the job of training scientific language models becomes highly nontrivial. In this paper, we initiate steps to tackle this issue. We introduce an extensible and lightweight toolkit, LMFlow, which aims to simplify the domain- and task-aware finetuning of general foundation models. LMFlow offers a complete finetuning workflow for a foundation model to support specialized training with limited computing resources. Furthermore, it supports continuous pretraining, instruction tuning, parameter-efficient finetuning, alignment tuning, inference acceleration, long context generalization, model customization, and even multimodal finetuning, along with carefully designed and extensible APIs. This toolkit has been thoroughly tested and is available at https://github.com/OptimalScale/LMFlow.

Key facts. Cited by 58 papers in the map (data through 7 Oct 2026). Builds on 39 of its 71 references that are in the map. First posted on arXiv 21 Jun 2023.

Builds on

39 of 71 references.

References · 39

  1. 2022Training language models to follow instructions with human feedbackcited by 15,712
  2. 2017Proximal Policy Optimization Algorithmscited by 14,441
  3. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  4. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  5. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
  6. 2020Measuring Massive Multitask Language Understandingcited by 7,768
  7. 2021On the Opportunities and Risks of Foundation Modelscited by 3,961
  8. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,747
  9. 2022Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackcited by 3,634
  10. 2022FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awarenesscited by 3,611
  11. 2023QLoRA: Efficient Finetuning of Quantized LLMscited by 3,355
  12. 2022Scaling Instruction-Finetuned Language Modelscited by 2,997
27 more
  1. 2022Self-Instruct: Aligning Language Models with Self-Generated Instructionscited by 2,674
  2. 2022BLOOM: A 176B-Parameter Open-Access Multilingual Language Modelcited by 1,968
  3. 2019BioBERT: a pre-trained biomedical language representation model for biomedical text miningcited by 1,935
  4. 2022Fast Inference from Transformers via Speculative Decodingcited by 1,615
  5. 2021Multitask Prompted Training Enables Zero-Shot Task Generalizationcited by 1,462
  6. 2019SciBERT: A Pretrained Language Model for Scientific Textcited by 1,404
  7. 2020What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Examscited by 1,324
  8. 2019PubMedQA: A Dataset for Biomedical Research Question Answeringcited by 1,271
  9. 2023Large Language Models are not Fair Evaluatorscited by 1,050
  10. 2021A General Language Assistant as a Laboratory for Alignmentcited by 1,023
  11. 2019Publicly Available Clinical BERT Embeddingscited by 995
  12. 2023The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Onlycited by 755
  13. 2022Galactica: A Large Language Model for Sciencecited by 736
  14. 2023Instruction Tuning with GPT-4cited by 676
  15. 2023RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignmentcited by 672
  16. 2022MedMCQA : A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answeringcited by 525
  17. 2019ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmissioncited by 487
  18. 2021ZeRO-Offload: Democratizing Billion-Scale Model Trainingcited by 339
  19. 2023MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Datacited by 282
  20. 2023HuatuoGPT, towards Taming Language Model to Be a Doctorcited by 211
  21. 2020Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPOcited by 184
  22. 2023DetGPT: Detect What You Need via Reasoningcited by 112
  23. 2023Do We Still Need Clinical Language Models?cited by 97
  24. 2023PMC-LLaMA: Towards Building Open-source Language Models for Medicinecited by 87
  25. 2023Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use Casescited by 85
  26. 2019On the Weaknesses of Reinforcement Learning for Neural Machine Translationcited by 82
  27. 2020Explaining Relationships Between Scientific Documentscited by 35

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 15; 2024: 27; 2025: 11; 2026: 5.

58 papers.

Sort:

By area:

  1. 2024LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Modelscited by 1,442
  2. 2023Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-Constraintcited by 346
  3. 2024SWIFT:A Scalable lightWeight Infrastructure for Fine-Tuningcited by 345
  4. 2024RLHF Workflow: From Reward Modeling to Online RLHFcited by 265
  5. 2023LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Modelscited by 195
  6. 2023Mitigating the Alignment Tax of RLHFcited by 181
  7. 2024Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewardscited by 145
  8. 2023UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecastingcited by 139
  9. 2023A Survey of Large Language Models in Medicine: Progress, Application, and Challengecited by 123
  10. 2024MLLM-Protector: Ensuring MLLM's Safety without Hurting Performancecited by 111
  11. 2023R-Tuning: Instructing Large Language Models to Say `I Don't Know'cited by 106
  12. 2024ARGS: Alignment as Reward-Guided Searchcited by 99
38 more
  1. 2024Hymba: A Hybrid-head Architecture for Small Language Modelscited by 95
  2. 2024Towards Building Multilingual Language Model for Medicinecited by 91
  3. 2024LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuningcited by 88
  4. 2023Towards Mitigating Hallucination in Large Language Models via Self-Reflectioncited by 81
  5. 2024Strengthening Multimodal Large Language Model with Bootstrapped Preference Optimizationcited by 75
  6. 2023EvalLM: Interactive Evaluation of Large Language Model Prompts on User-Defined Criteriacited by 73
  7. 2023ChatCounselor: A Large Language Models for Mental Health Supportcited by 44
  8. 2024Towards Evaluating and Building Versatile Large Language Models for Medicinecited by 38
  9. 2025Evaluation of Best-of-N Sampling Strategies for Language Model Alignmentcited by 38
  10. 2023MarineGPT: Unlocking Secrets of Ocean to the Publiccited by 23
  11. 2024Feel-Good Thompson Sampling for Contextual Dueling Banditscited by 23
  12. 2026How RLHF Amplifies Sycophancycited by 20
  13. 2025A Survey on Agentic Multimodal Large Language Modelscited by 19
  14. 2023B-Coder: Value-Based Deep Reinforcement Learning for Program Synthesiscited by 16
  15. 2025Nemotron-Flash: Towards Latency-Optimal Hybrid Small Language Modelscited by 15
  16. 2024AstroLLaMA-Chat: Scaling AstroLLaMA with Conversational and Diverse Datasetscited by 13
  17. 2023Evaluating Large Language Models for Radiology Natural Language Processingcited by 12
  18. 2024Dialectical Alignment: Resolving the Tension of 3H and Security Threats of LLMscited by 11
  19. 2024FIRST: Teach A Reliable Large Language Model Through Efficient Trustworthy Distillationcited by 11
  20. 2024KnowledgeSG: Privacy-Preserving Synthetic Text Generation with Knowledge Distillation from Servercited by 11
  21. 2024CMoralEval: A Moral Evaluation Benchmark for Chinese Large Language Modelscited by 9
  22. 2024PropaInsight: Toward Deeper Understanding of Propaganda in Terms of Techniques, Appeals, and Intentcited by 9
  23. 2024Empowering Segmentation Ability to Multi-modal Large Language Modelscited by 8
  24. 2024AdaPPA: Adaptive Position Pre-Fill Jailbreak Attack Approach Targeting LLMscited by 8
  25. 2023Enabling Language Models to Implicitly Learn Self-Improvementcited by 7
  26. 2026SLAM-LLM: A Modular, Open-Source Multimodal Large Language Model Framework and Best Practice for Speech, Language, Audio and Music Processingcited by 7
  27. 2024AstroMLab 2: AstroLLaMA-2-70B Model and Benchmarking Specialised LLMs for Astronomycited by 6
  28. 2024FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guaranteescited by 6
  29. 2025BiasFilter: An Inference-Time Debiasing Framework for Large Language Modelscited by 6
  30. 2025Better Convergence Guarantees for Sign-Based Momentum Methodscited by 6
  31. 2025Unbiased Gradient Low-Rank Projectioncited by 6
  32. 2023Learning Descriptive Image Captioning via Semipermeable Maximum Likelihood Estimationcited by 4
  33. 2024Enhancing Data Quality in Federated Fine-Tuning of Foundation Modelscited by 4
  34. 2025Mitigating Length Bias in RLHF through a Causal Lenscited by 4
  35. 2026StoSignSGD: Unbiased Structural Stochasticity Fixes SignSGD for Training Large Language Modelscited by 4
  36. 2023CoLLiE: Collaborative Training of Large Language Models in an Efficient Waycited by 3
  37. 2024Balancing Speciality and Versatility: A Coarse to Fine Framework for Mitigating Catastrophic Forgetting in Large Language Modelscited by 3
  38. 2024Bridge-Coder: Unlocking LLMs' Potential to Overcome Language Gaps in Low-Resource Codecited by 3

50 most cited of 58 All 58 (JSON)

Similar, not cited

Close in wording, no citation either way

  1. 2025A Survey on Post-training of Large Language Models
  2. 2026ArXiv-to-Model: A Practical Study of Scientific LM Training
  3. 2025Optimising Language Models for Downstream Tasks: A Post-Training Perspective
  4. 2024DeepSeek LLM: Scaling Open-Source Language Models with Longtermism
  5. 2024Let the Expert Stick to His Last: Expert-Specialized Fine-Tuning for Sparse Architectural Large Language Models
  6. 2025LLM Post-Training: A Deep Dive into Reasoning Large Language Models
  7. 2025A Survey on Large Language Models with some Insights on their Capabilities and Limitations
  8. 2025ResearchGPT: Benchmarking and Training LLMs for End-to-End Computer Science Research Workflows