Copertina

Pre-Trained Vision-Language Models as Partial Annotators

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wang, Qian-Wei, Xie, Yuqiu, Zhang, Letian, Liu, Zimo, Xia, Shu-Tao
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Fine-tuning Pre-trained Vision-Language Models in a Human-Annotation-Free Manner
di: Wang, Qian-Wei, et al.
Pubblicazione: (2026)

Bridging Weakly-Supervised Learning and VLM Distillation: Noisy Partial Label Learning for Efficient Downstream Adaptation
di: Wang, Qian-Wei, et al.
Pubblicazione: (2025)

Explicit Uncertainty Modeling for Active CLIP Adaptation with Dual Prompt Tuning
di: Wang, Qian-Wei, et al.
Pubblicazione: (2026)

Chain-of-Models Pre-Training: Rethinking Training Acceleration of Vision Foundation Models
di: Fan, Jiawei, et al.
Pubblicazione: (2026)

HQA-VLAttack: Towards High Quality Adversarial Attack on Vision-Language Pre-Trained Models
di: Liu, Han, et al.
Pubblicazione: (2026)

Avoid Wasted Annotation Costs in Open-set Active Learning with Pre-trained Vision-Language Model
di: Heo, Jaehyuk, et al.
Pubblicazione: (2024)

3D-Agent:Tri-Modal Multi-Agent Collaboration for Scalable 3D Object Annotation
di: Zhang, Jusheng, et al.
Pubblicazione: (2026)

Low-hallucination Synthetic Captions for Large-Scale Vision-Language Model Pre-training
di: Zhang, Xinsong, et al.
Pubblicazione: (2025)

Benchmarking Multi-Image Understanding in Vision and Language Models: Perception, Knowledge, Reasoning, and Multi-Hop Reasoning
di: Zhao, Bingchen, et al.
Pubblicazione: (2024)

Holmes: Towards Effective and Harmless Model Ownership Verification to Personalized Large Vision Models via Decoupling Common Features
di: Zhu, Linghui, et al.
Pubblicazione: (2025)

InstAP: Instance-Aware Vision-Language Pre-Train for Spatial-Temporal Understanding
di: Kumar, Ashutosh, et al.
Pubblicazione: (2026)

PromptEcho: Annotation-Free Reward from Vision-Language Models for Text-to-Image Reinforcement Learning
di: Liu, Jinlong, et al.
Pubblicazione: (2026)

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving
di: Sha, Lin, et al.
Pubblicazione: (2026)

InfiniteVL: Synergizing Linear and Sparse Attention for Highly-Efficient, Unlimited-Input Vision-Language Models
di: Tao, Hongyuan, et al.
Pubblicazione: (2025)

Training-Free Unsupervised Prompt for Vision-Language Models
di: Long, Sifan, et al.
Pubblicazione: (2024)

PPU-Bench:Real World Benchmark for Personalized Partial Unlearning in Vision Language Models
di: Guang, Jiahui, et al.
Pubblicazione: (2026)

Multimodal Fusion with Pre-Trained Model Features in Affective Behaviour Analysis In-the-wild
di: Wen, Zhuofan, et al.
Pubblicazione: (2024)

Do Pre-trained Vision-Language Models Encode Object States?
di: Newman, Kaleb, et al.
Pubblicazione: (2024)

DeVAn: Dense Video Annotation for Video-Language Models
di: Liu, Tingkai, et al.
Pubblicazione: (2023)

VVS: Accelerating Speculative Decoding for Visual Autoregressive Generation via Partial Verification Skipping
di: Dong, Haotian, et al.
Pubblicazione: (2025)

Med-UniC: Unifying Cross-Lingual Medical Vision-Language Pre-Training by Diminishing Bias
di: Wan, Zhongwei, et al.
Pubblicazione: (2023)

Open-Vocabulary Panoptic Segmentation Using BERT Pre-Training of Vision-Language Multiway Transformer Model
di: Chen, Yi-Chia, et al.
Pubblicazione: (2024)

Robotic Environmental State Recognition with Pre-Trained Vision-Language Models and Black-Box Optimization
di: Kawaharazuka, Kento, et al.
Pubblicazione: (2024)

Energy-Latency Manipulation of Multi-modal Large Language Models via Verbose Samples
di: Gao, Kuofeng, et al.
Pubblicazione: (2024)

Unleashing the Potential of Vision-Language Pre-Training for 3D Zero-Shot Lesion Segmentation via Mask-Attribute Alignment
di: Jiang, Yankai, et al.
Pubblicazione: (2024)

Natural Reflection Backdoor Attack on Vision Language Model for Autonomous Driving
di: Liu, Ming, et al.
Pubblicazione: (2025)

Reinforcing Spatial Reasoning in Vision-Language Models with Interwoven Thinking and Visual Drawing
di: Wu, Junfei, et al.
Pubblicazione: (2025)

VLKEB: A Large Vision-Language Model Knowledge Editing Benchmark
di: Huang, Han, et al.
Pubblicazione: (2024)

ForgeVLA: Federated Vision-Language-Action Learning without Language Annotations
di: Zhou, Yuhao, et al.
Pubblicazione: (2026)

Black-Box Adversarial Attack on Vision Language Models for Autonomous Driving
di: Wang, Lu, et al.
Pubblicazione: (2025)

VLM-AutoDrive: Post-Training Vision-Language Models for Safety-Critical Autonomous Driving Events
di: Bhat, Mohammad Qazim, et al.
Pubblicazione: (2026)

Attention-Guided Patch-Wise Sparse Adversarial Attacks on Vision-Language-Action Models
di: Zhang, Naifu, et al.
Pubblicazione: (2025)

Efficient Vision-and-Language Pre-training with Text-Relevant Image Patch Selection
di: Ye, Wei, et al.
Pubblicazione: (2024)

TRIPS: Efficient Vision-and-Language Pre-training with Text-Relevant Image Patch Selection
di: Jiang, Chaoya, et al.
Pubblicazione: (2023)

Synthesizing Efficient Data with Diffusion Models for Person Re-Identification Pre-Training
di: Niu, Ke, et al.
Pubblicazione: (2024)

EchoBench: Benchmarking Sycophancy in Medical Large Vision-Language Models
di: Yuan, Botai, et al.
Pubblicazione: (2025)

Grounded Knowledge-Enhanced Medical Vision-Language Pre-training for Chest X-Ray
di: Deng, Qiao, et al.
Pubblicazione: (2024)

GMMFormer: Gaussian-Mixture-Model Based Transformer for Efficient Partially Relevant Video Retrieval
di: Wang, Yuting, et al.
Pubblicazione: (2023)

TernaryCLIP: Efficiently Compressing Vision-Language Models with Ternary Weights and Distilled Knowledge
di: Zhang, Shu-Hao, et al.
Pubblicazione: (2025)

Can Medical Vision-Language Pre-training Succeed with Purely Synthetic Data?
di: Liu, Che, et al.
Pubblicazione: (2024)