Structural Anchor Pruning: Training-Free Multi-Vector Compression for Visual Document Retrieval

arXiv:2601.20107 · cs.CV, cs.CL, cs.IR · Submitted 2026-01-27 · Read on arXiv

cs.CV, cs.CL, cs.IR

Submitted: 2026-01-27

Updated: 2026-08-29

Terminology

• Pruning — 58× in this paper · explained in 4 episodes
• Benchmark — 29× in this paper · explained in 2 episodes
• Embeddings — 28× in this paper · explained in 2 episodes
• Alignment — 23× in this paper · explained in 1 episode
• Calibration — 23× in this paper · explained in 7 episodes
• Score Retention — 20× in this paper
• Fidelity — 15× in this paper · explained in 2 episodes
• Aggregation — 13× in this paper · explained in 1 episode
• Structural Anchor Pruning — 10× in this paper
• Clustering — 9× in this paper · explained in 2 episodes
• Visual Document Retrieval — 9× in this paper
• Ablation — 6× in this paper · explained in 1 episode
• Robustness — 5× in this paper · explained in 5 episodes
• Adaptation — 4× in this paper · explained in 1 episode
• Core — 4× in this paper · explained in 2 episodes
• RAG — 3× in this paper · explained in 3 episodes
• Attention Mechanism — 2× in this paper · explained in 2 episodes
• Computational overhead — 2× in this paper · explained in 2 episodes
• Redundancy — 2× in this paper · explained in 2 episodes
• Representation Learning — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Mask Generation — 1× in this paper · explained in 2 episodes
• Matryoshka Representation Learning — 1× in this paper
• Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes

Sources

• Qwen2.5-VL Technical Report
• PaliGemma: A versatile 3B VLM for transfer
• Token Merging: Your ViT But Faster
• ColPali: Efficient Document Retrieval with Vision Language Models
• Towards Storage-Efficient Visual Document Retrieval: An Empirical Study on Reducing Patch-Level Embeddings
• ViDoRe Benchmark V2: Raising the Bar for Visual Retrieval
• Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
• Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model
• Sculpting the Vector Space: Towards Efficient Multi-Vector Visual Document Retrieval via Prune-then-Merge Framework
• DocPruner: A Storage-Efficient Framework for Multi-Vector Visual Document Retrieval via Adaptive Patch-Level Embedding Pruning
• SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference

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