LLM Fine-Tuning

LLM: Large Language Model

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42 papers in the last four weeks, up 83% on the four weeks before. 0.4% of all new papers.

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Enhancing Fitness Intelligence through Domain-Specific LLM Post-Training
Jul 2, 2026Xingtao Zhao, Tian Yang, Han JiangDomain Adaptation LLM Fine-Tuning
School of Cyber Science and Technology Beihang University Beijing, China · School of Information Renmin University of China Beijing, China
TUDUM: A Turkish-Thinking Reasoning Pipeline for Qwen3.5-27B
Jul 2, 2026Baran Bingol, Bahaeddin TurkogluLLM Fine-Tuning LLM Mathematical Reasoning
Department of Artificial Intelligence and Data Engineering Faculty of Engineering Ankara University Ankara, Türkiye
Epistemic Goggles: A Pretrained Module that Induces an Epistemic Frame via Gradient Editing
Jul 2, 2026Joshua PenmanLLM Fine-Tuning Framing Effects in Language Models
Independent Researcher
Token Geometry
Jul 1, 2026Kathan ShahLanguage Model Pretraining LLM Fine-Tuning
Preprint.
ZO-Act: Efficient Zeroth-Order Fine-Tuning via One-Shot Activation-Informed Low-Rank Subspaces
Jul 1, 2026Xun Dong, Yibo Xu, Naigang Wang +3Zeroth-Order Optimization LLM Fine-Tuning
University at Albany, SUNY · IBM T. J. Watson Research Center
CORA: Per-Slice Coherent Orthogonal Rotation for SVD-based Low-Rank Adaptation
Jun 30, 2026Pengcheng Wang, Ziran Liu, Wei Wang +1LLM Fine-Tuning Low-Rank Matrix Decomposition
Purdue University · Shanghai Institute for Mathematics and Interdisciplinary Sciences / Fudan University · Futurewei Technologies, Inc.
Cross-lingual Relation Extraction with Large Language Models: Zero-Shot, Few-Shot, and Fine-Tuned Evaluation on Romanian
Jun 30, 2026Dragos-Mitrut Vasile, Elena-Simona Apostol, Stefan-Adrian Toma +2Relation Extraction LLM Fine-Tuning
National University of Science and Technology POLITEHNICA Bucharest, Splaiul Independent,ei 313, Bucures,ti 060042, Romania · Military Technical Academy ‘Ferdinand I’, Bulevardul George Cos,buc 39-49, 050141, Bucharest, Romania · Freie Universität Berlin, Arnimallee 14, Berlin, 14195, Germany +2
Nonlinearity-Aware LoRA: Structured Gate Adaptation under Low-Rank Constraints
Jun 30, 2026Shuai Yuan, Sudong Cai, Bingzhi Chen +4LLM Fine-Tuning Low-Rank Adaptation
1Beijing Institute of Technology, Zhuhai · 2The Hong Kong Polytechnic University · 3The University of Osaka +1
Think in English, Answer in Korean: Efficient Adaptation of Multilingual Tool-Using Agents
Jun 30, 2026Utsav Garg, Sungjin Hong, Jason Jung +6Multilingual Language Models LLM Fine-Tuning
1Cohere
Evil Spectra: How Optimisers can Amplify or Suppress Emergent Misalignment
Jun 30, 2026Jason R. Brown, Patrick Leask, Lev McKinneyLLM Fine-Tuning Emergent Misalignment in Language Models
Astra Fellows Program University of Cambridge · Astra Fellows Program Durham University · Astra Fellows Program University of Toronto
Fora: From Weight-Space to Function-Space Protection in Capability-Preserving Fine-Tuning
Jun 30, 2026Rui Zhou, Tianci XieFine-Tuning LLM Fine-Tuning
Dalian University of Technology · Zhejiang University
Towards Physical Intuitions for Alignment Dynamics: A Case Study With Randomness Crystallization
Jun 29, 2026Kunal Samanta, Ari Holtzman, Peter WestLLM Alignment LLM Fine-Tuning
University of British Columbia · University of Chicago
Evolution Fine-Tuning: Learning to Discover Across 371 Optimization Tasks
Jun 27, 2026Young-Jun Lee, Seungone Kim, Minki Kang +5Supervised Fine-Tuning Evolutionary Optimization
University of Minnesota · Carnegie Mellon University · KAIST +3
Fine-Tuning General-Purpose Large Language Models for Agricultural Applications:A Reproducible Framework and Evaluation Protocol Based on Qwen3-8B
Jun 27, 2026Zhaoyang Li, Ruijie Zhang, Jiaqi Liu +1LLM Fine-Tuning
1Sanya University · 2Hebei International Studies University
Beyond the Mean: Three-Axis Fidelity for Aligning LLM-Based Survey Simulators from Small Pilot Data
Jun 27, 2026Eun Cheol Choi, Youngrae Kim, Prabhu Pugalenthi +2LLM Alignment LLM Fine-Tuning
University of Southern California, CA, USA.
The Heterogeneous Safety Impacts of Benign Multilingual Fine-Tuning
Jun 27, 2026Will Hawkins, Kaivalya Rawal, Jonathan Rystrøm +8LLM Safety Benchmarks Multilingual Language Model Evaluation
Oxford Internet Institute, University of Oxford · Hasso Plattner Institute, University of Potsdam · Chinese University of Hong Kong +2
Low-Agreeableness Persona Conditioning for Safe LLM Fine-Tuning
Jun 26, 2026Austin MY Cheung, Yi YangLLM Fine-Tuning LLM Safety Alignment
Hong Kong University of Science and Technology
Fine-tuning a multimodal large language model for clinician-grade autism behavioral scoring from short home videos
Jun 25, 2026Mohammadmahdi Honarmand, Parnian Azizian, Aaron Kline +9Autism Spectrum Disorder LLM Fine-Tuning
Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA · Department of Pediatrics, Stanford University, Stanford, CA 94305, USA · Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA +2
Causal Connections: Leveraging Multilingual Fine-Tuning for Financial QA@FinCausal 2026
Jun 25, 2026Akash Kumar Gautam, Serhii Hamotskyi, Christian HänigRelation Extraction LLM Fine-Tuning
Anhalt University of Applied Sciences
Inherited Circuits, Learned Semantics: How Fine-Tuning Creates Evasion Vulnerabilities Invisible to Standard Evaluation
Jun 25, 2026Ryan FettermanAdversarial Attacks LLM Fine-Tuning
Cisco Talos
Reasoning Quality Emerges Early: Data Curation for Reasoning Models
Jun 25, 2026Hongyi Henry Jin, Wenhan Yang, Meysam Ghaffari +2LLM Fine-Tuning Training Data Selection
Department of Computer Science, University of California Los Angeles (UCLA), California, USA · Optum AI, UnitedHealth Group, Minneapolis, Minnesota, USA
EvoOptiGraph: Weakness-Driven Coevolution via Graph-Based Structural Generation for Optimization Modeling
Jun 25, 2026Qingcan Kang, Mingyang Liu, Xiaojin Fu +3LLM Fine-Tuning Synthetic Data Generation for Language Models
Huawei Noah’s Ark Lab · Department of Computer Science, City University of Hong Kong
Soft Token Alignment for Cross-Lingual Reasoning
Jun 25, 2026Jiayi He, Jungsoo Park, Wei Xu +1Multilingual Language Models Cross-Lingual Reasoning in Language Models
Georgia Institute of Technology
Detect, Unlearn, Restore: Defending Text Summarization Models Against Data Poisoning
Jun 24, 2026Poojitha Thota, Shirin NilizadehLLM Auditing LLM Fine-Tuning
The University of Texas at Arlington Arlington, Texas, USA
Riazi-8B: An Urdu Large Language Model for Mathematical Reasoning
Jun 24, 2026Azher Ali, Ibtsam Haider, Raja Khurram Shahzad +2Numerical Reasoning in Language Models LLM Fine-Tuning
School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Islamabad, Pakistan · Department of Communication, Quality Management and Information Systems, Mid Sweden University, Ostersund, Sweden
Improved Large Language Diffusion Models
Jun 24, 2026Shen Nie, Qiyang Min, Shaoxuan Xu +7Language Model Pretraining Masked Diffusion Models
Gaoling School of Artificial Intelligence, Renmin University of China · Beijing Key Laboratory of Research on Large Models and Intelligent Governance · Engineering Research Center of Next-Generation Intelligent Search and Recommendation, MOE +1
Randomized YaRN Improves Length Generalization for Long-Context Reasoning
Jun 22, 2026Manas Mehta, Fangcong Yin, Greg DurrettLong-Context Language Modeling LLM Fine-Tuning
New York University
POTracker: Optimizing Large Language Models for Standard-Compliant Power Outage Report Generation
Jun 22, 2026Hung Phan, Aniroop Naladala, Dubey Avanindra +3LLM Fine-Tuning Structured Output Generation
Iowa State University · Oak Ridge Nat. Laboratory
Do LLM Embedding Spaces Recover Expert Structure?
Jun 22, 2026Yixuan Zhu, Zhenke Duan, Fanghen LiLLM Fine-Tuning Mental Health
Zhongnan University of Economics and Law
Skin-Deep: A Geometric Diagnostic for Alignment Fragility in Large Language Model Representations
Jun 21, 2026Dongyub Jude Lee, Jungseob Lee, Seungyoon Lee +5LLM Interpretability LLM Fine-Tuning
Zoom Communications · Korea University · Yonsei University +1

Jul 2, 2026, cs.AIJ/K move · Enter open · S save

Enhancing Fitness Intelligence through Domain-Specific LLM Post-Training

Xingtao Zhao, Tian Yang, Han Jiang

School of Cyber Science and Technology Beihang University Beijing, China · School of Information Renmin University of China Beijing, China

Domain Adaptation LLM Fine-Tuning Domain Adaptation for LLMs LLM Post-Training

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Scientific Fitness Coaching (SFC) is typically delivered by human professionals, making it costly and inaccessible to many. While recent advances in Large Language Models (LLMs) show considerable promise for more inclusive fitness coaching, directly deploying prevailing general-purpose LLMs in SFC reveals critical limitations. These models often lack sufficient domain-specific knowledge integration, leading to weak performance on complex SFC scenarios. In this paper, we introduce FitOne, a series of fitness LLMs (with 8B and 32B parameters) designed to improve reliability and domain specialization for SFC applications. Built upon the Qwen3 foundation models, FitOne is developed through a three-stage post-training pipeline consisting of continual pre-training, supervised fine-tuning, and reinforcement learning, using large-scale, high-quality datasets derived from rigorous knowledge engineering. We conduct comprehensive evaluations of FitOne on professional fitness certification exams, including ACSM-EP and NSCA-CSCS, as well as general capabilities such as knowledge reasoning and instruction following. Experimental results show that, while retaining strong general capabilities, FitOne-8B/32B achieves average improvements of up to 10.09%/9.29% and 12.73%/7.01% on the ACSM-EP and NSCA-CSCS exams, respectively, compared with the Qwen3 base models. Furthermore, in-depth ablation studies confirm the necessity of each training stage, highlighting the pipeline's effectiveness in balancing domain expertise enhancement with general ability retention. We believe this research advances LLM systems toward more reliable fitness intelligence and will inspire future research on developing domain-specific LLMs.

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