DVD: Dynamic Vector Decoding for Efficient MLLM-based Perception

arXiv:2610.12266 · cs.CV, cs.AI · Submitted 2026-10-08 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-10-08

Updated: 2026-10-08

Project page: https://almoonysl.github.io/projects/DVD

Terminology

• Grounding — 73× in this paper · explained in 3 episodes
• Quantization — 15× in this paper · explained in 12 episodes
• Latent Space — 14× in this paper · explained in 7 episodes
• Benchmark — 12× in this paper · explained in 2 episodes
• Dynamic Vector Decoding — 12× in this paper
• Representation Learning — 7× in this paper · explained in 2 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Accuracy — 5× in this paper · explained in 1 episode
• Decode — 4× in this paper · explained in 2 episodes
• Computational overhead — 3× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Ablation study — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Latent Representation — 2× in this paper · explained in 2 episodes
• Semantic Understanding — 2× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Multimodal Dataset — 1× in this paper · explained in 2 episodes
• Point Clouds — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Segmentation Masks — 1× in this paper · explained in 2 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes
• Variational Bayes — 1× in this paper · explained in 2 episodes
• Vision-language models — 1× in this paper · explained in 2 episodes

Sources

• Qwen Technical Report
• Qwen3-VL Technical Report
• Qwen2.5-VL Technical Report
• ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Data
• Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic
• Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
• WeDetect: Fast Open-Vocabulary Object Detection as Retrieval
• Seed1.5-VL Technical Report
• Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models
• Auto-Encoding Variational Bayes
• Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement
• Decoupled Weight Decay Regularization
• DeepSeek-VL: Towards Real-World Vision-Language Understanding
• Towards Pixel-Level VLM Perception via Simple Points Prediction
• Chameleon: Mixed-Modal Early-Fusion Foundation Models
• Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
• Kimi K2.5: Visual Agentic Intelligence
• SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features
• Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
• InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

Related papers

• Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
• AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
• Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models