Towards Efficient Large Vision-Language Models: A Comprehensive Survey on Inference Strategies
Fuente:
arXiv
Saved in:
| Main Authors: | Pathak, Surendra, Han, Bo |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
ASAP: Attention-Shift-Aware Pruning for Efficient LVLM Inference
by: Pathak, Surendra, et al.
Published: (2026)
by: Pathak, Surendra, et al.
Published: (2026)
A Survey on Hallucination in Large Vision-Language Models
by: Liu, Hanchao, et al.
Published: (2024)
by: Liu, Hanchao, et al.
Published: (2024)
Towards Statistical Factuality Guarantee for Large Vision-Language Models
by: Li, Zhuohang, et al.
Published: (2025)
by: Li, Zhuohang, et al.
Published: (2025)
A Comprehensive Information-Decomposition Analysis of Large Vision-Language Models
by: Xiu, Lixin, et al.
Published: (2026)
by: Xiu, Lixin, et al.
Published: (2026)
MMIE: Massive Multimodal Interleaved Comprehension Benchmark for Large Vision-Language Models
by: Xia, Peng, et al.
Published: (2024)
by: Xia, Peng, et al.
Published: (2024)
Towards Efficient Vision-Language Tuning: More Information Density, More Generalizability
by: Hao, Tianxiang, et al.
Published: (2023)
by: Hao, Tianxiang, et al.
Published: (2023)
How Vision-Language Tasks Benefit from Large Pre-trained Models: A Survey
by: Qi, Yayun, et al.
Published: (2024)
by: Qi, Yayun, et al.
Published: (2024)
Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension
by: Wang, Xiyao, et al.
Published: (2024)
by: Wang, Xiyao, et al.
Published: (2024)
EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models
by: Wang, Zekun, et al.
Published: (2025)
by: Wang, Zekun, et al.
Published: (2025)
Language Models as Black-Box Optimizers for Vision-Language Models
by: Liu, Shihong, et al.
Published: (2023)
by: Liu, Shihong, et al.
Published: (2023)
Mostly Text, Smart Visuals: Asymmetric Text-Visual Pruning for Large Vision-Language Models
by: Li, Sijie, et al.
Published: (2026)
by: Li, Sijie, et al.
Published: (2026)
Revisiting Compositionality in Dual-Encoder Vision-Language Models: The Role of Inference
by: Miranda, Imanol, et al.
Published: (2026)
by: Miranda, Imanol, et al.
Published: (2026)
ETA: Evaluating Then Aligning Safety of Vision Language Models at Inference Time
by: Ding, Yi, et al.
Published: (2024)
by: Ding, Yi, et al.
Published: (2024)
Lever LM: Configuring In-Context Sequence to Lever Large Vision Language Models
by: Yang, Xu, et al.
Published: (2023)
by: Yang, Xu, et al.
Published: (2023)
Shotluck Holmes: A Family of Efficient Small-Scale Large Language Vision Models For Video Captioning and Summarization
by: Luo, Richard, et al.
Published: (2024)
by: Luo, Richard, et al.
Published: (2024)
Vision Mamba: A Comprehensive Survey and Taxonomy
by: Liu, Xiao, et al.
Published: (2024)
by: Liu, Xiao, et al.
Published: (2024)
Matryoshka Query Transformer for Large Vision-Language Models
by: Hu, Wenbo, et al.
Published: (2024)
by: Hu, Wenbo, et al.
Published: (2024)
JailbreakZoo: Survey, Landscapes, and Horizons in Jailbreaking Large Language and Vision-Language Models
by: Jin, Haibo, et al.
Published: (2024)
by: Jin, Haibo, et al.
Published: (2024)
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models
by: Xia, Peng, et al.
Published: (2024)
by: Xia, Peng, et al.
Published: (2024)
MultiTrust: A Comprehensive Benchmark Towards Trustworthy Multimodal Large Language Models
by: Zhang, Yichi, et al.
Published: (2024)
by: Zhang, Yichi, et al.
Published: (2024)
Memory-Space Visual Prompting for Efficient Vision-Language Fine-Tuning
by: Jie, Shibo, et al.
Published: (2024)
by: Jie, Shibo, et al.
Published: (2024)
S-GRPO: Unified Post-Training for Large Vision-Language Models
by: Yan, Yuming, et al.
Published: (2026)
by: Yan, Yuming, et al.
Published: (2026)
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models
by: Zhou, Yiyang, et al.
Published: (2023)
by: Zhou, Yiyang, et al.
Published: (2023)
TroL: Traversal of Layers for Large Language and Vision Models
by: Lee, Byung-Kwan, et al.
Published: (2024)
by: Lee, Byung-Kwan, et al.
Published: (2024)
Overconfidence is Key: Verbalized Uncertainty Evaluation in Large Language and Vision-Language Models
by: Groot, Tobias, et al.
Published: (2024)
by: Groot, Tobias, et al.
Published: (2024)
Mamba in Vision: A Comprehensive Survey of Techniques and Applications
by: Rahman, Md Maklachur, et al.
Published: (2024)
by: Rahman, Md Maklachur, et al.
Published: (2024)
Rethinking RL Scaling for Vision Language Models: A Transparent, From-Scratch Framework and Comprehensive Evaluation Scheme
by: Ma, Yan, et al.
Published: (2025)
by: Ma, Yan, et al.
Published: (2025)
TLDR: Token-Level Detective Reward Model for Large Vision Language Models
by: Fu, Deqing, et al.
Published: (2024)
by: Fu, Deqing, et al.
Published: (2024)
Towards Grounded Visual Spatial Reasoning in Multi-Modal Vision Language Models
by: Rajabi, Navid, et al.
Published: (2023)
by: Rajabi, Navid, et al.
Published: (2023)
Debiasing Large Vision-Language Models by Ablating Protected Attribute Representations
by: Ratzlaff, Neale, et al.
Published: (2024)
by: Ratzlaff, Neale, et al.
Published: (2024)
Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models
by: Zheng, Kening, et al.
Published: (2024)
by: Zheng, Kening, et al.
Published: (2024)
Aligning Modalities in Vision Large Language Models via Preference Fine-tuning
by: Zhou, Yiyang, et al.
Published: (2024)
by: Zhou, Yiyang, et al.
Published: (2024)
Progressive Multi-granular Alignments for Grounded Reasoning in Large Vision-Language Models
by: Le, Quang-Hung, et al.
Published: (2024)
by: Le, Quang-Hung, et al.
Published: (2024)
Few-Shot Adversarial Prompt Learning on Vision-Language Models
by: Zhou, Yiwei, et al.
Published: (2024)
by: Zhou, Yiwei, et al.
Published: (2024)
A Survey on Multimodal Large Language Models
by: Yin, Shukang, et al.
Published: (2023)
by: Yin, Shukang, et al.
Published: (2023)
DRESS: Instructing Large Vision-Language Models to Align and Interact with Humans via Natural Language Feedback
by: Chen, Yangyi, et al.
Published: (2023)
by: Chen, Yangyi, et al.
Published: (2023)
Patch-Prompt Aligned Bayesian Prompt Tuning for Vision-Language Models
by: Liu, Xinyang, et al.
Published: (2023)
by: Liu, Xinyang, et al.
Published: (2023)
A Survey on Data Augmentation in Large Model Era
by: Zhou, Yue, et al.
Published: (2024)
by: Zhou, Yue, et al.
Published: (2024)
Hierarchical Safety Realignment: Lightweight Restoration of Safety in Pruned Large Vision-Language Models
by: Li, Yue, et al.
Published: (2025)
by: Li, Yue, et al.
Published: (2025)
A Vision Check-up for Language Models
by: Sharma, Pratyusha, et al.
Published: (2024)
by: Sharma, Pratyusha, et al.
Published: (2024)
Similar Items
-
ASAP: Attention-Shift-Aware Pruning for Efficient LVLM Inference
by: Pathak, Surendra, et al.
Published: (2026) -
A Survey on Hallucination in Large Vision-Language Models
by: Liu, Hanchao, et al.
Published: (2024) -
Towards Statistical Factuality Guarantee for Large Vision-Language Models
by: Li, Zhuohang, et al.
Published: (2025) -
A Comprehensive Information-Decomposition Analysis of Large Vision-Language Models
by: Xiu, Lixin, et al.
Published: (2026) -
MMIE: Massive Multimodal Interleaved Comprehension Benchmark for Large Vision-Language Models
by: Xia, Peng, et al.
Published: (2024)