LSVD: Loss-Aware Low-Rank Approximation for Efficient Low-Precision Vision-Language Models
cs.LG
Submitted: 2026-05-30
Updated: 2026-10-21
Terminology
Sources
- Palu: Compressing KV-Cache with Low-Rank Projection
- VLRM: Vision-Language Models act as Reward Models for Image Captioning
- GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers
- The Llama 3 Herd of Models
- Language model compression with weighted low-rank factorization
- SearchLVLMs: A Plug-and-Play Framework for Augmenting Large Vision-Language Models by Searching Up-to-Date Internet Knowledge
- SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models
- MBQ: Modality-Balanced Quantization for Large Vision-Language Models
- AdaSVD: Adaptive Singular Value Decomposition for Large Language Models
- A Survey on Hallucination in Large Vision-Language Models
- SpinQuant: LLM quantization with learned rotations
- SmolVLM: Redefining small and efficient multimodal models
- OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models
- QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks
- The LLM Surgeon
- Q-VLM: Post-training Quantization for Large Vision-Language Models
- Surgical-LVLM: Learning to Adapt Large Vision-Language Model for Grounded Visual Question Answering in Robotic Surgery
- Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
- Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives
- SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression
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