Enhancing Vision-Language Model Pre-training with Image-text Pair Pruning Based on Word Frequency
Fuente:
arXiv
Saved in:
| Main Authors: | Liang, Mingliang, Larson, Martha |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Frequency Is What You Need: Considering Word Frequency When Text Masking Benefits Vision-Language Model Pre-training
by: Liang, Mingliang, et al.
Published: (2024)
by: Liang, Mingliang, et al.
Published: (2024)
Centered Masking for Language-Image Pre-Training
by: Liang, Mingliang, et al.
Published: (2024)
by: Liang, Mingliang, et al.
Published: (2024)
Pre-trained Vision-Language Models Learn Discoverable Visual Concepts
by: Zang, Yuan, et al.
Published: (2024)
by: Zang, Yuan, et al.
Published: (2024)
COSMOS: Cross-Modality Self-Distillation for Vision Language Pre-training
by: Kim, Sanghwan, et al.
Published: (2024)
by: Kim, Sanghwan, et al.
Published: (2024)
Pre-trained Language Models Do Not Help Auto-regressive Text-to-Image Generation
by: Zhang, Yuhui, et al.
Published: (2023)
by: Zhang, Yuhui, et al.
Published: (2023)
Uni-Mlip: Unified Self-supervision for Medical Vision Language Pre-training
by: Bawazir, Ameera, et al.
Published: (2024)
by: Bawazir, Ameera, et al.
Published: (2024)
One Prompt Word is Enough to Boost Adversarial Robustness for Pre-trained Vision-Language Models
by: Li, Lin, et al.
Published: (2024)
by: Li, Lin, et al.
Published: (2024)
Superpixel Semantics Representation and Pre-training for Vision-Language Task
by: Zhang, Siyu, et al.
Published: (2023)
by: Zhang, Siyu, et al.
Published: (2023)
Vision Learners Meet Web Image-Text Pairs
by: Zhao, Bingchen, et al.
Published: (2023)
by: Zhao, Bingchen, et al.
Published: (2023)
Words or Vision: Do Vision-Language Models Have Blind Faith in Text?
by: Deng, Ailin, et al.
Published: (2025)
by: Deng, Ailin, et al.
Published: (2025)
ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models
by: Sung, Yi-Lin, et al.
Published: (2023)
by: Sung, Yi-Lin, et al.
Published: (2023)
Efficient Pruning of Text-to-Image Models: Insights from Pruning Stable Diffusion
by: Ramesh, Samarth N, et al.
Published: (2024)
by: Ramesh, Samarth N, et al.
Published: (2024)
Pre-trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control
by: Gupta, Gunshi, et al.
Published: (2024)
by: Gupta, Gunshi, et al.
Published: (2024)
On Pre-training of Multimodal Language Models Customized for Chart Understanding
by: Fan, Wan-Cyuan, et al.
Published: (2024)
by: Fan, Wan-Cyuan, et al.
Published: (2024)
Vision-Language Model Based Handwriting Verification
by: Chauhan, Mihir, et al.
Published: (2024)
by: Chauhan, Mihir, et al.
Published: (2024)
Robust Pre-Training of Medical Vision-and-Language Models with Domain-Invariant Multi-Modal Masked Reconstruction
by: Filvantorkaman, Melika, et al.
Published: (2026)
by: Filvantorkaman, Melika, et al.
Published: (2026)
Gesture2Text: A Generalizable Decoder for Word-Gesture Keyboards in XR Through Trajectory Coarse Discretization and Pre-training
by: Shen, Junxiao, et al.
Published: (2024)
by: Shen, Junxiao, et al.
Published: (2024)
VisPlay: Self-Evolving Vision-Language Models from Images
by: He, Yicheng, et al.
Published: (2025)
by: He, Yicheng, et al.
Published: (2025)
Is Pre-training Truly Better Than Meta-Learning?
by: Miranda, Brando, et al.
Published: (2023)
by: Miranda, Brando, et al.
Published: (2023)
Efficient Pre-training for Localized Instruction Generation of Videos
by: Batra, Anil, et al.
Published: (2023)
by: Batra, Anil, et al.
Published: (2023)
Index-Preserving Lightweight Token Pruning for Efficient Document Understanding in Vision-Language Models
by: Son, Jaemin, et al.
Published: (2025)
by: Son, Jaemin, et al.
Published: (2025)
Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement
by: Wang, Xiyao, et al.
Published: (2024)
by: Wang, Xiyao, et al.
Published: (2024)
Enhancing Financial VQA in Vision Language Models using Intermediate Structured Representations
by: Srivastava, Archita, et al.
Published: (2025)
by: Srivastava, Archita, et al.
Published: (2025)
Analyzing Fine-Grained Alignment and Enhancing Vision Understanding in Multimodal Language Models
by: Jiang, Jiachen, et al.
Published: (2025)
by: Jiang, Jiachen, et al.
Published: (2025)
Exploring Transfer Learning in Medical Image Segmentation using Vision-Language Models
by: Poudel, Kanchan, et al.
Published: (2023)
by: Poudel, Kanchan, et al.
Published: (2023)
Dynamic Cluster Data Sampling for Efficient and Long-Tail-Aware Vision-Language Pre-training
by: Liang, Mingliang, et al.
Published: (2026)
by: Liang, Mingliang, et al.
Published: (2026)
Preserving Pre-trained Representation Space: On Effectiveness of Prefix-tuning for Large Multi-modal Models
by: Kim, Donghoon, et al.
Published: (2024)
by: Kim, Donghoon, et al.
Published: (2024)
EmbodiedMidtrain: Bridging the Gap between Vision-Language Models and Vision-Language-Action Models via Mid-training
by: Du, Yiyang, et al.
Published: (2026)
by: Du, Yiyang, et al.
Published: (2026)
Compensating Distribution Drifts in Class-incremental Learning of Pre-trained Vision Transformers
by: Rao, Xuan, et al.
Published: (2025)
by: Rao, Xuan, et al.
Published: (2025)
VCM: Vision Concept Modeling Based on Implicit Contrastive Learning with Vision-Language Instruction Fine-Tuning
by: Luo, Run, et al.
Published: (2025)
by: Luo, Run, et al.
Published: (2025)
In-Depth and In-Breadth: Pre-training Multimodal Language Models Customized for Comprehensive Chart Understanding
by: Fan, Wan-Cyuan, et al.
Published: (2025)
by: Fan, Wan-Cyuan, et al.
Published: (2025)
Mitigating Object Hallucination in Large Vision-Language Models via Image-Grounded Guidance
by: Zhao, Linxi, et al.
Published: (2024)
by: Zhao, Linxi, et al.
Published: (2024)
Symmetrical Visual Contrastive Optimization: Aligning Vision-Language Models with Minimal Contrastive Images
by: Wu, Shengguang, et al.
Published: (2025)
by: Wu, Shengguang, et al.
Published: (2025)
World-to-Words: Grounded Open Vocabulary Acquisition through Fast Mapping in Vision-Language Models
by: Ma, Ziqiao, et al.
Published: (2023)
by: Ma, Ziqiao, et al.
Published: (2023)
GQKVA: Efficient Pre-training of Transformers by Grouping Queries, Keys, and Values
by: Javadi, Farnoosh, et al.
Published: (2023)
by: Javadi, Farnoosh, et al.
Published: (2023)
Preserving Multi-Modal Capabilities of Pre-trained VLMs for Improving Vision-Linguistic Compositionality
by: Oh, Youngtaek, et al.
Published: (2024)
by: Oh, Youngtaek, et al.
Published: (2024)
CoViPAL: Layer-wise Contextualized Visual Token Pruning for Large Vision-Language Models
by: Tang, Zicong, et al.
Published: (2025)
by: Tang, Zicong, et al.
Published: (2025)
GFlowVLM: Enhancing Multi-step Reasoning in Vision-Language Models with Generative Flow Networks
by: Kang, Haoqiang, et al.
Published: (2025)
by: Kang, Haoqiang, et al.
Published: (2025)
Multi-modal Vision Pre-training for Medical Image Analysis
by: Rui, Shaohao, et al.
Published: (2024)
by: Rui, Shaohao, et al.
Published: (2024)
Effective Backdoor Mitigation in Vision-Language Models Depends on the Pre-training Objective
by: Verma, Sahil, et al.
Published: (2023)
by: Verma, Sahil, et al.
Published: (2023)
Similar Items
-
Frequency Is What You Need: Considering Word Frequency When Text Masking Benefits Vision-Language Model Pre-training
by: Liang, Mingliang, et al.
Published: (2024) -
Centered Masking for Language-Image Pre-Training
by: Liang, Mingliang, et al.
Published: (2024) -
Pre-trained Vision-Language Models Learn Discoverable Visual Concepts
by: Zang, Yuan, et al.
Published: (2024) -
COSMOS: Cross-Modality Self-Distillation for Vision Language Pre-training
by: Kim, Sanghwan, et al.
Published: (2024) -
Pre-trained Language Models Do Not Help Auto-regressive Text-to-Image Generation
by: Zhang, Yuhui, et al.
Published: (2023)