A linearized framework and a new benchmark for model selection for fine-tuning

29 January 2021

Hao Li

Papers citing "A linearized framework and a new benchmark for model selection for fine-tuning"

35 / 35 papers shown

Title
Optimal Transport-Guided Source-Free Adaptation for Face Anti-Spoofing Z. Li Tianchen Zhao Xiang Xu Zheng Zhang Zhihua Li Xuanbai Chen Q. Zhang Alessandro Bergamo Anil K. Jain Yifan Xing 37 0 0 29 Mar 2025
k-NN as a Simple and Effective Estimator of Transferability Moein Sorkhei Christos Matsoukas Johan Fredin Haslum Kevin Smith 57 0 0 24 Mar 2025
Capability Instruction Tuning: A New Paradigm for Dynamic LLM Routing Yi-Kai Zhang De-Chuan Zhan Han-Jia Ye ALM ELM LRM 41 1 0 24 Feb 2025
Transferring Knowledge from Large Foundation Models to Small Downstream Models Shikai Qiu Boran Han Danielle C. Maddix Shuai Zhang Yuyang Wang Andrew Gordon Wilson 38 1 0 11 Jun 2024
Model Selection with Model Zoo via Graph Learning Ziyu Li Hilco van der Wilk Danning Zhan Megha Khosla A. Bozzon Rihan Hai 46 1 0 05 Apr 2024
CMAT: A Multi-Agent Collaboration Tuning Framework for Enhancing Small Language Models Xuechen Liang Meiling Tao Yinghui Xia Yiting Xie Jun Wang JingSong Yang LLMAG 33 12 0 02 Apr 2024
Which Model to Transfer? A Survey on Transferability Estimation Yuhe Ding Bo Jiang Aijing Yu Aihua Zheng Jian Liang 45 4 0 23 Feb 2024
Selecting Large Language Model to Fine-tune via Rectified Scaling Law Haowei Lin Baizhou Huang Haotian Ye Qinyu Chen Zihao Wang Sujian Li Jianzhu Ma Xiaojun Wan James Zou Yitao Liang 87 20 0 04 Feb 2024
Simple Transferability Estimation for Regression Tasks Cuong N. Nguyen Phong Tran L. Ho Vu C. Dinh Anh Tran Tal Hassner Cuong V Nguyen 11 2 0 01 Dec 2023
On Characterizing the Evolution of Embedding Space of Neural Networks using Algebraic Topology Suryaka Suresh Bishshoy Das V. Abrol Sumantra Dutta Roy 14 2 0 08 Nov 2023
Towards Robust and Efficient Continual Language Learning Adam Fisch Amal Rannen-Triki Razvan Pascanu J. Bornschein Angeliki Lazaridou E. Gribovskaya MarcÁurelio Ranzato CLL 26 1 0 11 Jul 2023
Kernels, Data & Physics Francesco Cagnetta Deborah Oliveira Mahalakshmi Sabanayagam Nikolaos Tsilivis Julia Kempe 25 0 0 05 Jul 2023
Model Spider: Learning to Rank Pre-Trained Models Efficiently Yi-Kai Zhang Ting Huang Yao-Xiang Ding De-Chuan Zhan Han-Jia Ye 28 23 0 06 Jun 2023
Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models Guillermo Ortiz-Jiménez Alessandro Favero P. Frossard MoMe 51 110 0 22 May 2023
Train/Test-Time Adaptation with Retrieval L. Zancato Alessandro Achille Tian Yu Liu Matthew Trager Pramuditha Perera Stefano Soatto TTA OOD 24 12 0 25 Mar 2023
TRAK: Attributing Model Behavior at Scale Sung Min Park Kristian Georgiev Andrew Ilyas Guillaume Leclerc A. Madry TDI 30 127 0 24 Mar 2023
Your representations are in the network: composable and parallel adaptation for large scale models Yonatan Dukler Alessandro Achille Hao Yang Varsha Vivek L. Zancato Benjamin Bowman Avinash Ravichandran Charless C. Fowlkes A. Swaminathan Stefano Soatto 28 3 0 07 Mar 2023
The Role of Pre-training Data in Transfer Learning R. Entezari Mitchell Wortsman O. Saukh M. Shariatnia Hanie Sedghi Ludwig Schmidt 46 20 0 27 Feb 2023
Supervision Complexity and its Role in Knowledge Distillation Hrayr Harutyunyan A. S. Rawat A. Menon Seungyeon Kim Surinder Kumar 22 12 0 28 Jan 2023
Cold Posteriors through PAC-Bayes Konstantinos Pitas Julyan Arbel 23 5 0 22 Jun 2022
SHiFT: An Efficient, Flexible Search Engine for Transfer Learning Cédric Renggli Xiaozhe Yao Luka Kolar Luka Rimanic Ana Klimovic Ce Zhang OOD 35 4 0 04 Apr 2022
Demystifying the Neural Tangent Kernel from a Practical Perspective: Can it be trusted for Neural Architecture Search without training? J. Mok Byunggook Na Ji-Hoon Kim Dongyoon Han Sungroh Yoon AAML 42 23 0 28 Mar 2022
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning Wei Huang Chunrui Liu Yilan Chen Tianyu Liu R. Xu BDL MLT 19 2 0 04 Feb 2022
DIVA: Dataset Derivative of a Learning Task Yonatan Dukler Alessandro Achille Giovanni Paolini Avinash Ravichandran M. Polito Stefano Soatto 14 5 0 18 Nov 2021
Scalable Diverse Model Selection for Accessible Transfer Learning Daniel Bolya Rohit Mittapalli Judy Hoffman OODD 27 41 0 12 Nov 2021
Deep Active Learning by Leveraging Training Dynamics Haonan Wang Wei Huang Ziwei Wu A. Margenot Hanghang Tong Jingrui He AI4CE 27 33 0 16 Oct 2021
Newer is not always better: Rethinking transferability metrics, their peculiarities, stability and performance Shibal Ibrahim Natalia Ponomareva Rahul Mazumder AAML 106 16 0 13 Oct 2021
Representation Consolidation for Training Expert Students Zhizhong Li Avinash Ravichandran Charless C. Fowlkes M. Polito Rahul Bhotika Stefano Soatto 16 6 0 16 Jul 2021
Unsupervised Model Drift Estimation with Batch Normalization Statistics for Dataset Shift Detection and Model Selection Won-Jo Lee Seokhyun Byun Jooeun Kim Minje Park Kirill Chechil AI4TS 21 2 0 01 Jul 2021
Frustratingly Easy Transferability Estimation Long-Kai Huang Ying Wei Yu Rong Qiang Yang Junzhou Huang 30 57 0 17 Jun 2021
What can linearized neural networks actually say about generalization? Guillermo Ortiz-Jiménez Seyed-Mohsen Moosavi-Dezfooli P. Frossard 29 43 0 12 Jun 2021
What to Pre-Train on? Efficient Intermediate Task Selection Clifton A. Poth Jonas Pfeiffer Andreas Rucklé Iryna Gurevych 19 94 0 16 Apr 2021
Which Model to Transfer? Finding the Needle in the Growing Haystack Cédric Renggli André Susano Pinto Luka Rimanic J. Puigcerver C. Riquelme Ce Zhang Mario Lucic 29 23 0 13 Oct 2020
Selecting Relevant Features from a Multi-domain Representation for Few-shot Classification Nikita Dvornik Cordelia Schmid Julien Mairal VLM 178 24 0 20 Mar 2020
Transferability and Hardness of Supervised Classification Tasks Anh Tran Cuong V Nguyen Tal Hassner 134 164 0 21 Aug 2019