Fine-Tuning

Follow this topic Ask about this topic

Latest papers 205

31 papers in the last four weeks, up 72% on the four weeks before. 0.2% of all new papers.

All topics

An Investigation of Model Coherence: Narrow Finetunes Contradict Themselves Under Resampling
Oct 8, 2026Robert Graham, Yariv Barsheshat, Phil Blandfort +1Reasoning Consistency in Language Models Self-Consistency in Language Models
Independent · Predictably Weird · Amazon
MAP4CS: A Multi-dimensional Data Pruning Framework for Efficient Code Retriever Fine-tuning
Oct 8, 2026Yuxuan Chen, Mingwei Liu, Guangsheng Ou +4Training Data Selection Dataset Pruning
School of Software Engineering, Sun Yat-sen University, China
SP-DocReader: Difference-Aware Self-Play for Precise Document OCR
Oct 8, 2026Wenjie Liao, Xiaohui Song, Liangjie Zhao +1Optical Character Recognition Vision-Language Models
Guangdong OPPO Mobile Telecommunications Corp.,Ltd · Adelaide University
Stability-Plasticity Balance via Singular-Vector Selection in LLM Continual Learning
Oct 8, 2026Lingxiang Wang, Hainan Zhang, Liang Pang +2Continual Learning for LLMs Parameter-Efficient Fine-Tuning
School of Artificial Intelligence, Beihang University · Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing · Institute of Computing Technology, Chinese Academy of Sciences
Comprehensive Evaluation and Fine-Tuning of Foundational Cell Nuclei Segmentation Models in Renal Pathology
Oct 6, 2026Ruijie Wu, Junlin Guo, Ruining Deng +4Medical Imaging Foundation Models Fine-Tuning
Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA · Department of Radiology, Weill Cornell Medicine, New York, NY 10021, USA · Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN 37235, USA +2
HeuFouFT: Task-Guided Metaheuristic Coordinate Search for Fourier Fine-Tuning
Oct 5, 2026Ruiheng Wang, Yubo Hou, Yakun Zhu +3Fine-Tuning LLM Fine-Tuning
Beihang University, Beijing, China · Shanghai Jiao Tong University, Shanghai, China · VinUniversity, Hanoi, Vietnam
Pre-training interventions, ex post facto: Grafting model beliefs across checkpoints
Sep 30, 2026Peter Nutter, Dani Roytburg, Clément Dumas +2Fine-Tuning LLM Alignment
ETH Zurich · MATS · Carnegie Mellon University +2
Bayesian Fine-tuning Yields Language Models that are as Bayesian as their Beliefs Allow
Sep 30, 2026Polina Tsvilodub, Andreas Waldis, Linlu Qiu +2Fine-Tuning LLM Fine-Tuning
University of Tübingen · Massachusetts Institute of Technology · New York University
Fenchel Tilting: Weighted Correction for Efficient Finetuning of Generative Models
Sep 30, 2026Maksim Bobrin, Maksim Zhdanov, Dmitry DylovDiffusion Model Alignment Constrained Generative Modeling
AXXX · Applied AI Institute · MBZUAI
Alignment via Training Against Probes Without Losing Monitorability
Sep 29, 2026Lena Libon, Alexander Panfilov, Ben Rank +3Fine-Tuning LLM Safety Alignment
ETH Zurich · ELLIS Institute Tübingen, MPI for Intelligent Systems, Tübingen AI Center
On-Policy Parameter Update Direction Underlies Generalization in LLM Post-Training
Sep 29, 2026Shufan Shen, Zhongni Hou, Junshu Sun +5LLM Post-Training Fine-Tuning
State Key Lab. of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences · University of Chinese Academy Sciences · Meituan
Narrow Multimodal Fine-Tuning Can Induce Emergent Misalignment
Sep 28, 2026Shunchang Liu, Lukas Fluri, Xin Chen +1Vision-Language Models Fine-Tuning
ETH Zürich · EPFL · Aalto University +1
Layer-Informed Fine-Tuning via Three-Stage Functional Segmentation of LLMs
Sep 28, 2026Junning Shao, Siwei Wang, Zhixuan FangLLM Fine-Tuning Fine-Tuning
Tsinghua University, Beijing, China · Microsoft Research Asia, Beijing, China · Shanghai Qi Zhi Institute, Shanghai, China
Statistical Benefits of Fine-Tuning from Pretrained Initialization in Diagonal Linear Networks
Sep 28, 2026Alexandre Declèves, Etienne Boursier, Nicolas FlammarionFine-Tuning Deep Linear Networks
TML, EPFL, Lausanne, Switzerland · INRIA, LMO, Université Paris-Saclay, Orsay, France
Two-Timescale Fine-tuning Provably Learns New Features for Two-Layer ReLU Networks
Sep 28, 2026Etienne Boursier, Nicolas FlammarionRepresentation Learning Fine-Tuning
INRIA, LMO, Universit´e Paris-Saclay, Orsay, France · EPFL, Lausanne, Switzerland
MaskCoFT: Masked Co-Adaptive Fine-Tuning for Memory-Efficient MoE Inference
Sep 28, 2026Junfeng Wu, Zehao Fan, Hadjer Benmeziane +3Expert Offloading Mixture-of-Experts Language Models
Department of Industrial and Systems Engineering, Rensselaer Polytechnic Institute · Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute · IBM Research
Resource-Aware Parameter-Efficient Model Adaptation for Onboard High-Dimensional Data
Sep 27, 2026Qiyang Zhang, Xinhao Li, Lei Shi +4Fine-Tuning Low-Rank Adaptation
Beijing University of Posts and Telecommunications · Wuhan University · Communication University of China +1
A Light Bilevel Refinement Aligns Self-Supervised Representations for Stronger Task-Specific Learning
Sep 27, 2026Gustav Wagner Zakarias, Zheng-Hua TanFine-Tuning Bilevel Optimization
Aalborg University · Pioneer Centre for Artificial Intelligence, Denmark
Reuse or Relearn? A Spectral View of Earth Observation Foundation Models
Sep 26, 2026Mehmet Ozgur Turkoglu, Valerio Marsocci, Dominik J. Mühlematter +3Fine-Tuning Geospatial Foundation Models
SoFT: Soft Targets for Generalizable LLM Fine-Tuning
Sep 26, 2026Huihao Jing, Wenbin Hu, Shaojin Chen +7LLM Fine-Tuning Fine-Tuning
HKUST, HKUST-GZ
What Should We Freeze? Guarded Freezing: Connectivity Shapes the Fine-Tuning of Pretrained Models
Sep 26, 2026Leonel AguilarFine-Tuning Selective Fine-Tuning
Chair of Cognitive Science, ETH Zürich
Can One Adapted Model Do It All? Fine-Tuning Strategy Selection for Customer Support LLMs
Sep 23, 2026Md Tahmid Rahman Laskar, Xue-Yong Fu, Shashi Bhushan TNFine-Tuning Customer Support Automation
Dialpad Inc.
MIS-Bench: Benchmarking Multimodal LLMs for Psychotherapeutic Interpersonal Skills Assessment
Sep 19, 2026Yuhan Lu, Yi Yao, Hua Shen +2Clinical Language Model Evaluation Multimodal Model Evaluation
NYU Shanghai, New York University
Past, Future, All at Once: Mitigating Stability-Plasticity Dilemma via Post-hoc JANUS Rectification
Sep 17, 2026Zhilong Zheng, Letian Tao, Yang Guan +7Fine-Tuning Continual Learning
School of Vehicle and Mobility & College of AI, Tsinghua University · Didi Voyager Labs, DiDi Autonomous Driving
Learning from the Gap Between Pass@K and Pass@1
Sep 17, 2026Xuan Liu, Jingbin Qian, Haosheng ChenLLM Fine-Tuning Fine-Tuning
Shanghai Jiao Tong University · William Marsh Rice University · East China Normal University
Label-free steering: Compressing test-time reinforcement learning into bias-only subspaces
Sep 16, 2026Naveen Vakada, Mingyuan Li, Shaoxiong JiFine-Tuning Test-Time Adaptation of VLMs
University of Turku, Finland · ELLIS Institute Finland
ReDraft, Don't Just Distill: Reference-Driven Revision for Continual VLLM Post-Training
Sep 15, 2026Zhihao Zhang, Mingqi Wu, Qiaole Dong +15Fine-Tuning Multimodal Large Language Models
Fudan University · Shanghai Artificial Intelligence Laboratory · Tencent
Compute-Optimal Pretrain--Fine-tune in Ridge Gradient Descent
Sep 14, 2026Alex Buna, Fanghui Liu, Patrick RebeschiniFine-Tuning
Department of Statistics, University of Oxford, UK · School of Mathematical Sciences, Institute of Natural Sciences and MOE-LSC, Shanghai Jiao Tong University, China.
Shallow Beliefs: Synthetic document finetuning does not inoculate against emergent misalignment from reward hacking
Sep 14, 2026Arun Jose, Julian StastnyReward Hacking Fine-Tuning
Astra Fellowship · Redwood Research
Retrieval-Guided Fine-Tuning as Noisy Estimation: Risk bounds and Architectural Analysis
Sep 13, 2026Bhargav Lad, Yifan HaoFine-Tuning RAG Robustness
Department of Mathematics Indian Institute of Technology Delhi New Delhi, India · Department of Computer Science University of Illinois Urbana-Champaign Urbana, IL 61801

Oct 8, 2026, cs.AIJ/K move · Enter open · S save

An Investigation of Model Coherence: Narrow Finetunes Contradict Themselves Under Resampling

Robert Graham, Yariv Barsheshat, Phil Blandfort, Sabri Alouache

Independent · Predictably Weird · Amazon

Reasoning Consistency in Language Models Self-Consistency in Language Models Fine-Tuning

Open paper AskPDF arXiv

A large body of research measures model coherence based on output variance without adequately considering competing causes. We identify two such causes, ambiguity and indifference, and we introduce a set of 175 questions where contradicting answers cannot easily be explained by either. We then measure incoherence in terms of contradictions when resampling answers to the same question. In contrast to other methods our metric has high specificity, and only ranks models as incoherent when the issues are glaring. Even so, we find narrow finetunes score poorly. Inspecting inconsistencies flagged by our method, we find that model organisms from the literature display severe issues such as identity conflation, introspection failures and rationalizations. These findings suggest that the pathologies induced by narrow finetuning may limit what these models can tell us about coherent misaligned behaviour.