"model fine-tuning" Papers

23 papers found

$\mathcal{X}^2$-DFD: A framework for e$\mathcal{X}$plainable and e$\mathcal{X}$tendable Deepfake Detection

Yize Chen, Zhiyuan Yan, Guangliang Cheng et al.

NEURIPS 2025

A Large-scale Training Paradigm for Graph Generative Models

Yu Wang, Ryan Rossi, Namyong Park et al.

ICLR 2025
1
citations

An OpenMind for 3D Medical Vision Self-supervised Learning

Tassilo Wald, Constantin Ulrich, Jonathan Suprijadi et al.

ICCV 2025arXiv:2412.17041
12
citations

CAMEx: Curvature-aware Merging of Experts

Dung Viet Nguyen, Minh Nguyen, Luc Nguyen et al.

ICLR 2025arXiv:2502.18821
6
citations

Can LLMs Separate Instructions From Data? And What Do We Even Mean By That?

Egor Zverev, Sahar Abdelnabi, Soroush Tabesh et al.

ICLR 2025arXiv:2403.06833
48
citations

Can LLMs Solve Longer Math Word Problems Better?

Xin Xu, Tong Xiao, Zitong Chao et al.

ICLR 2025arXiv:2405.14804
26
citations

Detail-Preserving Latent Diffusion for Stable Shadow Removal

Jiamin Xu, Yuxin Zheng, Zelong Li et al.

CVPR 2025arXiv:2412.17630
7
citations

Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix

Ming Wen, Jiaqi Zhu, Yuedong Xu et al.

NEURIPS 2025arXiv:2507.09990

Escaping the SpuriVerse: Can Large Vision-Language Models Generalize Beyond Seen Spurious Correlations?

Yiwei Yang, Chung Peng Lee, Shangbin Feng et al.

NEURIPS 2025arXiv:2506.18322
3
citations

Flick: Empowering Federated Learning with Commonsense Knowledge

Ran Zhu, Mingkun Yang, Shiqiang Wang et al.

NEURIPS 2025

FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models

Yan Gao, Massimo R. Scamarcia, Javier Fernandez-Marques et al.

NEURIPS 2025arXiv:2506.02961
4
citations

Machine Unlearning via Simulated Oracle Matching

Kristian G Georgiev, Roy Rinberg, Sam Park et al.

ICLR 2025
3
citations

Persistent Pre-training Poisoning of LLMs

Yiming Zhang, Javier Rando, Ivan Evtimov et al.

ICLR 2025arXiv:2410.13722
38
citations

Singular Value Scaling: Efficient Generative Model Compression via Pruned Weights Refinement

Hyeonjin Kim, Jaejun Yoo

AAAI 2025paperarXiv:2412.17387
2
citations

Small Batch Size Training for Language Models: When Vanilla SGD Works, and Why Gradient Accumulation is Wasteful

Martin Marek, Sanae Lotfi, Aditya Somasundaram et al.

NEURIPS 2025arXiv:2507.07101
22
citations

Spend Wisely: Maximizing Post-Training Gains in Iterative Synthetic Data Bootstrapping

Pu Yang, Yunzhen Feng, Ziyuan Chen et al.

NEURIPS 2025spotlightarXiv:2501.18962
1
citations

Trade-offs in Image Generation: How Do Different Dimensions Interact?

Sicheng Zhang, Binzhu Xie, Zhonghao Yan et al.

ICCV 2025arXiv:2507.22100
2
citations

$\texttt{MoE-RBench}$: Towards Building Reliable Language Models with Sparse Mixture-of-Experts

Guanjie Chen, Xinyu Zhao, Tianlong Chen et al.

ICML 2024arXiv:2406.11353
6
citations

Adversarial Feature Map Pruning for Backdoor

Dong HUANG, Qingwen Bu

ICLR 2024arXiv:2307.11565
5
citations

Language Models as Science Tutors

Alexis Chevalier, Jiayi Geng, Alexander Wettig et al.

ICML 2024arXiv:2402.11111
15
citations

MGit: A Model Versioning and Management System

Wei Hao, Daniel Mendoza, Rafael Mendes et al.

ICML 2024arXiv:2307.07507
1
citations

Neural Lineage

Runpeng Yu, Xinchao Wang

CVPR 2024arXiv:2406.11129
7
citations

PoseGen: Learning to Generate 3D Human Pose Dataset with NeRF

Mohsen Gholami, Rabab Ward, Z. Jane Wang

AAAI 2024paperarXiv:2312.14915
3
citations