LLM Fine-Tuning

LLM: Large Language Model

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Overview

LLM fine-tuning studies how additional training can adapt a pretrained model to new tasks, specialized knowledge, languages, or desired behaviors. Common approaches include supervised fine-tuning on curated or synthetic examples, preference optimization and reinforcement learning, and parameter-efficient methods such as LoRA and QLoRA that update only a small part of the model. Researchers also develop data-selection methods and selective layer or neuron updates to reduce training cost, and evaluate results on settings such as reasoning, code generation, multilingual tasks, and domain-specific question answering. A central challenge is gaining reliable task performance without losing general abilities or safety; results depend on the data, model, and evaluation, and retrieval can sometimes be a better alternative for adding knowledge.

Latest papers

CardsList

758 papers76 papers in the last four weeks, up 15% on the four weeks before. 0.4% of all new papers.

  1. Parametric Knowledge in RAG-SFT for Domain-Specific Document Generation

    Mar 24, 2026Julian Oestreich, Maximilian Bley, Frank Binder +3Retrieval-Augmented GenerationLLM Fine-Tuning

    Institute for Applied Informatics (InfAI) at Leipzig University · CELUS GmbH, Munich

  2. Optimizing Small Language Models for NL2SQL via Chain-of-Thought Fine-Tuning

    Mar 24, 2026Anshul Solanki, Sanchit Latawa, Koushik Chakraborty +1Text-to-SQLFine-Tuning

    Google AI, Global Services Delivery

  3. AgriPestDatabase-v1.0: A Structured Insect Dataset for Training Agricultural Large Language Model

    Mar 24, 2026Yagizhan Bilal Durak, Ahsan Ul Islam, Shahidul Islam +3LLM Fine-TuningOn-Device Language Model Inference

    Sam Houston State University, Huntsville, TX, USA · Kennesaw State University, Kennesaw, GA, USA

  4. Enhancing Document-Level Machine Translation via Filtered Synthetic Corpora and Two-Stage LLM Adaptation

    Mar 23, 2026Ireh Kim, Tesia Sker, Chanwoo KimMachine TranslationDocument-Level MT

    Department of Artificial Intelligence, Korea University, Seoul, South Korea

  5. CurvZO: Adaptive Curvature-Guided Sparse Zeroth-Order Optimization for Efficient LLM Fine-Tuning

    Mar 23, 2026Shuo Wang, Ziyu Chen, Ming TangZeroth-Order OptimizationMemory-Efficient Fine-Tuning

    Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China. · Department of Mathematics, Southern University of Science and Technology, Shenzhen, China.

  6. mSFT: Addressing Dataset Mixtures Overfitting Heterogeneously in Multi-task SFT

    Mar 23, 2026Woosung Koh, Jeyoung Jeon, Youngjin Song +4LLM Fine-TuningSupervised Fine-Tuning

    KAIST AI · Yonsei University · Samsung Advanced Institute of Technology

  7. Understanding Contextual Recall in Transformers: How Finetuning Enables In-Context Reasoning over Pretraining Knowledge

    Mar 21, 2026Bhavya Vasudeva, Puneesh Deora, Alberto Bietti +2In-Context LearningImplicit Reasoning in Language Models

    University of Southern California · University of British Columbia · Flatiron Institute

  8. Alignment Whack-a-Mole : Finetuning Activates Verbatim Recall of Copyrighted Books in Large Language Models

    Mar 21, 2026Xinyue Liu, Niloofar Mireshghallah, Jane C. Ginsburg +1LLM AlignmentMemorization in Language Models

    Stony Brook University · Carnegie Mellon University · Columbia Law School

  9. MzansiText and MzansiLM: An Open Corpus and Decoder-Only Language Model for South African Languages

    Mar 21, 2026Anri Lombard, Simbarashe Mawere, Temi Aina +5African Language ProcessingMultilingual Language Models

    University of Cape Town, Cape Town, South Africa

  10. SAGE: Sustainable Agent-Guided Expert-tuning for Culturally Attuned Translation in Low-Resource Southeast Asia

    Mar 20, 2026Zhixiang Lu, Chong Zhang, Yulong Li +5Machine TranslationLow-Resource MT

    Xi’an Jiaotong-Liverpool University Suzhou, China · University of Liverpool Liverpool, United Kingdom · Mohamed bin Zayed University of Artificial Intelligence Abu Dhabi, United Arab Emirates

  11. KA2L: A Knowledge-Aware Active Learning Framework for LLMs

    Mar 18, 2026Haoxuan Yin, Chen Tang, Yangfan Wang +2Active LearningLLM Fine-Tuning

    Faculty of Computing, Harbin Institute of Technology, Harbin, 150001, China · Institute for Advanced Algorithms Research, Shanghai, 201306, China · National Key Laboratory of Smart Farm Technologies and Systems, Harbin, 150001, China

  12. An Efficient Heterogeneous Co-Design for Fine-Tuning on a Single GPU

    Mar 17, 2026Ruijia Yang, Zeyi WenFine-TuningMemory-Efficient Fine-Tuning

    HKUST(GZ) Guangzhou, China · HKUST Guangzhou, China

  13. W2T: LoRA Weights Already Know What They Can Do

    Mar 16, 2026Xiaolong Han, Ferrante Neri, Zijian Jiang +4Weight-Space LearningLow-Rank Adaptation

    University of Surrey · Stanford University · University of Notre Dame

  14. Fine-tuning MLLMs Without Forgetting Is Easier Than You Think

    Mar 15, 2026He Li, Yuhui Zhang, Xiaohan Wang +2LLM Fine-TuningMultimodal Large Language Models

    Stanford University · Tsinghua University

  15. IGU-LoRA: Adaptive Rank Allocation via Integrated Gradients and Uncertainty-Aware Scoring

    Mar 14, 2026Xuan Cui, Huiyue Li, Run Zeng +5LLM Fine-TuningLow-Rank Adaptation

    Chongqing Technology and Business University · Shanghai Jiao Tong University

  16. Aligning the Query Space: Greedy Information Projection for Language Model Data Selection

    Mar 14, 2026Victor Ye Dong, Kuan-Yun Lee, Jiamei Shuai +3LLM Fine-TuningInstruction-Tuning Data Selection

    Microsoft

  17. Benchmarking Large Language Models on Reference Extraction and Parsing in the Social Sciences and Humanities

    Mar 13, 2026Yurui Zhu, Giovanni Colavizza, Matteo RomanelloDocument Information ExtractionLLM Information Extraction

    Odoma LLC

  18. BERTology of Molecular Property Prediction

    Mar 13, 2026Mohammad Mostafanejad, Paul Saxe, T. Daniel CrawfordChemical Language ModelsMolecular Property Prediction

    Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, USA · Molecular Sciences Software Institute, Blacksburg, Virginia 24060, USA

  19. Neuron-Aware Data Selection In Instruction Tuning For Large Language Models

    Mar 13, 2026Xin Chen, Junchao Wu, Shu Yang +6Instruction-Tuning Data SelectionTraining Data Selection

    NLP2CT Lab, Department of Computer and Information Science, University of Macau · Artificial Intelligence Research Institute, Shenzhen University of Advanced Technology · National Key Laboratory for Novel Software Technology, Nanjing University +2

  20. DS2^2-Instruct: Domain-Specific Data Synthesis for Large Language Models Instruction Tuning

    Mar 13, 2026Ruiyao Xu, Noelle I. Samia, Han LiuSynthetic Data Generation for Language ModelsLLM Fine-Tuning

    Northwestern University

  21. Adapting Methods for Domain-Specific Japanese Small LMs: Scale, Architecture, and Quantization

    Mar 12, 2026Takato YasunoLanguage ModelingSmall Language Models

  22. Matching Features, Not Tokens: Energy-Based Fine-Tuning of Language Models

    Mar 12, 2026Samy Jelassi, Mujin Kwun, Rosie Zhao +5Fine-Tuning Language ModelsLLM Fine-Tuning

    Harvard University, Kempner Institute · MBZUAI · Microsoft Research New England

  23. Resurfacing Paralinguistic Awareness in Large Audio Language Models

    Mar 12, 2026Hao Yang, Minghan Wang, Tongtong Wu +3Audio-Language ModelsLLM Fine-Tuning

    Department of Data Science & AI, Monash University, Australia · Department of Computer Science, University College London, UK

  24. When Fine-Tuning Fails and when it Generalises: Role of Data Diversity and Mixed Training in LLM-based TTS

    Mar 11, 2026Anupam Purwar, Aditya ChoudharyTTS SynthesisText-to-Speech

    Sprinklr AI Gurugram, India

  25. GR-SAP: Generative Replay for Safety Alignment Preservation during Fine-Tuning

    Mar 10, 2026Zhouxiang Fang, Jiawei Zhou, Hanjie ChenSafety-Preserving Fine-Tuning of Language ModelsLLM Safety Alignment

    Rice University · Stony Brook University

  26. Mashup Learning: Faster Finetuning by Remixing Past Checkpoints

    Mar 10, 2026Sofia Maria Lo Cicero Vaina, Artem Chumachenko, Max RyabininLLM Fine-TuningLLM Training

    Together AI.

  27. ESAinsTOD: A Unified End-to-End Schema-Aware Instruction-Tuning Framework for Task-Oriented Dialog Modeling

    Mar 10, 2026Dechuan Teng, Chunlin Lu, Libo Qin +1Task-Oriented Dialogue SystemsInstruction Tuning

    Research Center for Social Computing and Information Retrieval, Harbin Institute of Technology, Harbin, China. · School of Computer Science and Engineering, Central South University, Changsha, China.

  28. Build, Borrow, or Just Fine-Tune? A Political Scientist's Guide to Choosing NLP Models

    Mar 10, 2026Shreyas MeherLLM Fine-TuningLanguage Modeling

    School of Social and Behavioural Sciences, Erasmus University Rotterdam

  29. Cognitively Layered Data Synthesis for Domain Adaptation of LLMs to Space Situational Awareness

    Mar 10, 2026Ding Linghu, Cheng Wang, Da Fan +6Space Situational AwarenessDomain Adaptation for LLMs

    Qian Xuesen Laboratory of Space Technology, China Academy of Space Technology, Beijing, China · China Academy of Space Technology, Beijing, China · State Key Laboratory of Space Information System and Integrated Application, Beijing, China

  30. Bioalignment: Measuring and Improving LLM Disposition Toward Biological Systems for AI Safety

    Mar 10, 2026Trent R Northen, Mingxun WangLLM AlignmentLLM Safety

    Bioaligned Labs · Lawrence Berkeley National Lab · Computer Science & Engineering Dept, UC Riverside