"linear probing" Papers
13 papers found
Conference
Assessing and Learning Alignment of Unimodal Vision and Language Models
Le Zhang, Qian Yang, Aishwarya Agrawal
CVPR 2025highlightarXiv:2412.04616
15
citations
Rethinking Self-Distillation: Label Averaging and Enhanced Soft Label Refinement with Partial Labels
Hyeonsu Jeong, Hye Won Chung
ICLR 2025arXiv:2402.10482
1
citations
Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning
Achleshwar Luthra, Tianbao Yang, Tomer Galanti
NEURIPS 2025arXiv:2506.04411
2
citations
The Dynamic Duo of Collaborative Masking and Target for Advanced Masked Autoencoder Learning
Shentong Mo
AAAI 2025paperarXiv:2412.17566
1
citations
Understanding Parametric and Contextual Knowledge Reconciliation within Large Language Models
Jun Zhao, Yongzhuo Yang, Xiang Hu et al.
NEURIPS 2025spotlight
Words in Motion: Extracting Interpretable Control Vectors for Motion Transformers
Omer Sahin Tas, Royden Wagner
ICLR 2025arXiv:2406.11624
4
citations
A Closer Look at the Few-Shot Adaptation of Large Vision-Language Models
Julio Silva-Rodríguez, Sina Hajimiri, Ismail Ben Ayed et al.
CVPR 2024arXiv:2312.12730
65
citations
Physics of Language Models: Part 3.1, Knowledge Storage and Extraction
Zeyuan Allen-Zhu, Yuanzhi Li
ICML 2024spotlightarXiv:2309.14316
244
citations
Q-Probe: A Lightweight Approach to Reward Maximization for Language Models
Kenneth Li, Samy Jelassi, Hugh Zhang et al.
ICML 2024arXiv:2402.14688
15
citations
Stochastic positional embeddings improve masked image modeling
Amir Bar, Florian Bordes, Assaf Shocher et al.
ICML 2024arXiv:2308.00566
6
citations
The First to Know: How Token Distributions Reveal Hidden Knowledge in Large Vision-Language Models?
Qinyu Zhao, Ming Xu, Kartik Gupta et al.
ECCV 2024arXiv:2403.09037
15
citations
The Linear Representation Hypothesis and the Geometry of Large Language Models
Kiho Park, Yo Joong Choe, Victor Veitch
ICML 2024arXiv:2311.03658
363
citations
What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks
Ching-Yun (Irene) Ko, Pin-Yu Chen, Payel Das et al.
ICML 2024