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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TalkTag: Fine-Grained Morphosyntactic Error Annotation for Transcribed Speech
Jun 1, 2026Shamira Venturini, Oliver Hennhöfer, Steffen Kinkel +1LLM Fine-Tuning LLM-Assisted Annotation
Karlsruhe Institute of Technology · Karlsruhe University of Applied Sciences · Karlsruhe Institute of Technology, Germany +1
AlphaToken: Decoupling Adaptation and Stability for Path-Aware Response Token Valuation in LLM Post-Training
Jun 1, 2026Liu Qing, Ou Wu, Yi DuLLM Fine-Tuning Language Model Post-Training
Hangzhou Institute for Advanced Study
Two to Tango: Coupled Task-Reference Selection for Safe LLM Fine-tuning
Jun 1, 2026Xinrui Chen, Jianhao Zhang, Ou Wu +1LLM Fine-Tuning Data Selection
Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences
LongAttnComp: Cross-Family Context Compression for Long-Context Reasoning
May 31, 2026Mengmeng Ji, Ravi Shanker Raju, Jonathan Lingjie Li +1LLM Compression LLM Fine-Tuning
SambaNova Systems, Inc. San Jose, CA, USA
Subliminal Learning is a LoRA Artifact
May 30, 2026Todd Nief, Harvey Yiyun Fu, Mark Muchane +1LLM Fine-Tuning Low-Rank Adaptation
Department of Computer Science, University of Chicago · Data Science Institute, University of Chicago
Escaping the Mode Lottery: Multi-Response Training Improves Language Model Generalization
May 30, 2026Hasan Amin, Kian Ahrabian, Ming Yin +1LLM Fine-Tuning OOD Generalization
Department of Computer Science Purdue University · Information Sciences Institute University of Southern California
Short-form Text Rewriting with Phi Silica
May 30, 2026Divya Tadimeti, Shawn Pan, Sameera Lanka +2LLM Fine-Tuning Small Language Models
Microsoft · Cambridge, USA · Redmond, USA
Isolating LLM Lexical Bias: A Curation-Free Triangulated Metric for Preference-Stage Learning
May 29, 2026Xiaoyang Ming, Jose Hernandez, Thomas Stephan JuzekLLM Alignment LLM Fine-Tuning
Florida State University
What Gets Unmasked First? Trajectory Analysis of Diffusion Models for Graph-to-Text Generation
May 29, 2026Qing Wang, Jacob Devasier, Chengkai LiMasked Diffusion Models LLM Fine-Tuning
The University of Texas at Arlington
Balanced LoRA: Removing Parameter Invariance to Accelerate Convergence
May 29, 2026Valérie Castin, Kimia Nadjahi, Pierre Ablin +1LLM Fine-Tuning Low-Rank Adaptation
1 ´Ecole Normale Sup´erieure PSL, Paris, France · 2CNRS · 3Apple, Paris, France.
DataShield: Safety-degrading Data Filtering for LLM Benign Instruction Fine-Tuning
May 29, 2026Junbo Zhang, Qianli Zhou, Xinyang Deng +3LLM Fine-Tuning Instruction-Tuning Data Selection
TRACE: Discovering Task-Specific Parameter via Adaptation-Aware Probing for Continual Fine-Tuning
May 29, 2026Xiaosong Han, Ke Chen, Xindi Dai +7Continual Learning for LLMs LLM Fine-Tuning
Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education · College of Computer Science and Technology, Jilin University Changchun, China · College of Software, Jilin University Changchun, China +3
Shortcuts in the Tail: Debiasing via Post-Hoc Spectral Compression of Fine-Tuning Updates
May 29, 2026Edward Sun, Dmitrii TroitskiiLLM Fine-Tuning Algorithmic Fairness
Department of Computer Science, UCLA, Los Angeles, CA, USA · Independent.
Fine-Tuning Improves Information Conveyance in Language Models
May 29, 2026Yuwei Cheng, Weiyi Tian, Haifeng XuLanguage Model Generation Evaluation LLM Fine-Tuning
Department of Data Science University of Chicago Chicago, IL 60637 · Department of Computer Science University of Chicago Chicago, IL 60637
The Long-Term Effects of Data Selection in LLM Fine-Tuning
May 28, 2026Yuxin Yang, Aoxiong Zeng, Xiangquan YangContinual Learning for LLMs LLM Fine-Tuning
Shanghai University · East China Normal University
Domain Adaptation and Reasoning Frameworks in Language Models: A Controlled Experiment with Historical Cosmology
May 28, 2026Francesco De BernardisDomain Adaptation LLM Fine-Tuning
Independent Researcher
Efficient Test-Time Finetuning of LLMs via Convex Reconstruction and Gradient Caching
May 28, 2026Alaa Khamis, Alaa MaaloufLLM Inference Efficiency Fine-Tuning
Department of Computer Science University of Haifa
How LoRA Remembers? A Parametric Memory Law for LLM Finetuning
May 28, 2026Ziwen Xu, Haiwen Hong, Linsong Yu +4Memorization in Language Models LLM Fine-Tuning
Zhejiang University · Alibaba Group
Harnessing non-adversarial robustness in large language models
May 28, 2026Qinghua Zhou, Ellina Aleshina, Andrey Lovyagin +6LLM Fine-Tuning Neural Network Robustness
International Joint Laboratory of AI for Industry, QUST, Qingdao, China · King’s College London, London, UK · Applied AI Institute, Moscow, Russia +2
Mask the Target: A Plug-and-Play Regularizer Against LoRA Forgetting
May 28, 2026Runze Xu, Arpit Garg, Hemanth Saratchandran +1Continual Learning for LLMs LLM Fine-Tuning
Australian Institute for Machine Learning Adelaide University Adelaide SA 5000
FoRA: Fisher-orthogonal Rank Adaptation for Parameter-Efficient Fine-Tuning
May 28, 2026Juneyoung Park, Seongbae Lee, Han-Sang Lee +6LLM Fine-Tuning Adapter Tuning
OptAI Inc · LG Uplus
Entropy-KL Divergence-based Token Masking: A Novel Approach for Selective Fine-tuning of Large Language Models
May 28, 2026Qi Liu, Mingdi Sun, Yongyi He +5Supervised Fine-Tuning Fine-Tuning
University of Science and Technology of China · Huawei Cloud
Diagnosing Harmful Continuation in Answer-Correct Long-CoT Training Traces
May 28, 2026Chen He, Yuhao Wu, Lei Wang +2Fine-Tuning LLM Fine-Tuning
University of Electronic Science and Technology of China · Singapore University of Technology and Design · Singapore Management University
Towards Reliable Multilingual LLMs-as-a-Judge: An Empirical Study
May 27, 2026Irune Zubiaga, Aitor Soroa, Rodrigo AgerriMultilingual Language Model Evaluation LLM-as-a-Judge
HiTZ Center - Ixa, University of the Basque Country EHU
RA-MoE: Routing-Aligned Fine-Tuning for Multilingual Adaptation of Mixture-of-Experts Models
May 27, 2026Guanzhi Deng, Kuan Wu, Haibo Wang +6Mixture-of-Experts Language Models LLM Fine-Tuning
City University of Hong Kong, Hong Kong, China · Carnegie Mellon University, Pittsburgh, USA · The University of Hong Kong, Hong Kong, China
SPARD: Defending Harmful Fine-Tuning Attack via Safety Projection with Relevance-Diversity Data Selection
May 27, 2026Shuhao Chen, Weisen Jiang, Yeqi Gong +5LLM Fine-Tuning LLM Safety Alignment
Department of Computer Science and Engineering, Southern University of Science and Technology · Department of Computer Science and Engineering, The Hong Kong University of Science and Technology · Department of Computer Science and Engineering, The Chinese University of Hong Kong +2
Fine-Tuned LLM as a Complementary Predictor Improving Ads System
May 27, 2026Hui Yang, Daiwei He, Kevin Jiang +20LLM Fine-Tuning Online Advertising
Pinterest, Inc., USA
Unsupervised Identification and Removal of Spurious Correlations During Fine-Tuning
May 26, 2026Ciarán M. Gilligan-Lee, Joseph Egan, Yuchen Zhu +1LLM Fine-Tuning Political Bias in Language Models
University College London · University College London† · Spotify
Learning to Translate from Soft to Hard LLM Prompts
May 26, 2026Pitipat Kongsomjit, Suryansh Goyal, Jacob WhitehillLLM Prompting LLM Interpretability
Worcester Polytechnic Institute
Gradient Transformer: Learning to Generate Updates for LLMs
May 26, 2026Binh-Nguyen Nguyen, Khang Tran, NhatHai Phan +1Privacy-Preserving Language Models LLM Fine-Tuning
Department of Data Science, New Jersey Institute of Technology, Newark, NJ, USA · Qatar Computing Research Institute, HBKU, Doha, Qatar

Jun 1, 2026, cs.CLJ/K move · Enter open · S save

TalkTag: Fine-Grained Morphosyntactic Error Annotation for Transcribed Speech

Shamira Venturini, Oliver Hennhöfer, Steffen Kinkel, Jannik Strötgen

Karlsruhe Institute of Technology · Karlsruhe University of Applied Sciences · Karlsruhe Institute of Technology, Germany+1

LLM Fine-Tuning LLM-Assisted Annotation Morphosyntactic Tagging

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Fine-grained morphosyntactic error annotation is important in clinical and developmental language research, yet it is labour-intensive, expert-dependent, and difficult to scale. We present TalkTag, an LLM-based lightweight tool fine-tuned to automate CHAT-style error annotation in spoken-language transcripts. Developed under conditions of extreme data scarcity using children's narrative data, the system shows the feasibility of linguistic analysis in low-resource settings. Our evaluation demonstrates that TalkTag produces encouragingly precise annotation while effectively identifying instances where linguistic ambiguity makes automated tagging genuinely complex. In summary, with TalkTag, we provide a scalable alternative to manual error annotation and practically viable support for morphosyntactic error annotation.

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Latest papers 509