mlsanityData to 14 Oct 2026

Vision Search Assistant: Empower Vision-Language Models as Multimodal Search Engines

arXiv 2410.21220 ↗First posted 28 Oct 2024cs.CV cs.AI cs.IRcited by 16

On the map: Multimodal LLMs / vision-language models → Document understanding and multimodal RAG

Abstract (arXiv)

Search engines enable the retrieval of unknown information with texts. However, traditional methods fall short when it comes to understanding unfamiliar visual content, such as identifying an object that the model has never seen before. This challenge is particularly pronounced for large vision-language models (VLMs): if the model has not been exposed to the object depicted in an image, it struggles to generate reliable answers to the user's question regarding that image. Moreover, as new objects and events continuously emerge, frequently updating VLMs is impractical due to heavy computational burdens. To address this limitation, we propose Vision Search Assistant, a novel framework that facilitates collaboration between VLMs and web agents. This approach leverages VLMs' visual understanding capabilities and web agents' real-time information access to perform open-world Retrieval-Augmented Generation via the web. By integrating visual and textual representations through this collaboration, the model can provide informed responses even when the image is novel to the system. Extensive experiments conducted on both open-set and closed-set QA benchmarks demonstrate that the Vision Search Assistant significantly outperforms the other models and can be widely applied to existing VLMs.

Key facts. Cited by 16 papers in the map (data through 14 Oct 2026). Placed in Document understanding and multimodal RAG, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 43 of its 47 references that are in the map. First posted on arXiv 28 Oct 2024.

Builds on

43 of 47 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024GPT-4V(ision) is a Generalist Web Agent, if Grounded3 Jan

Other references · 42

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  3. 2023Visual Instruction Tuningcited by 7,869
  4. 2023BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Modelscited by 6,137
  5. 2023Improved Baselines with Visual Instruction Tuningcited by 4,418
  6. 2022Flamingo: a Visual Language Model for Few-Shot Learningcited by 4,386
  7. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,824
  8. 2023Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detectioncited by 3,332
  9. 2024Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextcited by 3,224
  10. 2023MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Modelscited by 2,711
  11. 2023Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyondcited by 2,224
  12. 2020REALM: Retrieval-Augmented Language Model Pre-Trainingcited by 2,141
30 more
  1. 2021WebGPT: Browser-assisted question-answering with human feedbackcited by 1,745
  2. 2021Improving language models by retrieving from trillions of tokenscited by 1,293
  3. 2023Mind2Web: Towards a Generalist Agent for the Webcited by 1,242
  4. 2020Leveraging Passage Retrieval with Generative Models for Open Domain Question Answeringcited by 1,210
  5. 2023Kosmos-2: Grounding Multimodal Large Language Models to the Worldcited by 1,089
  6. 2024How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suitescited by 1,050
  7. 2022Atlas: Few-shot Learning with Retrieval Augmented Language Modelscited by 952
  8. 2022Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questionscited by 923
  9. 2020Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrievalcited by 849
  10. 2023REPLUG: Retrieval-Augmented Black-Box Language Modelscited by 792
  11. 2017Reading Wikipedia to Answer Open-Domain Questionscited by 777
  12. 2023MiniGPT-v2: large language model as a unified interface for vision-language multi-task learningcited by 625
  13. 2023LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Modelcited by 602
  14. 2023Language Is Not All You Need: Aligning Perception with Language Modelscited by 543
  15. 2020RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answeringcited by 413
  16. 2023A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesiscited by 353
  17. 2023MultiModal-GPT: A Vision and Language Model for Dialogue with Humanscited by 255
  18. 2020Distilling Knowledge from Reader to Retriever for Question Answeringcited by 226
  19. 2024DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learningcited by 214
  20. 2023OneLLM: One Framework to Align All Modalities with Languagecited by 187
  21. 2020Answering Complex Open-Domain Questions with Multi-Hop Dense Retrievalcited by 162
  22. 2023Meta-Transformer: A Unified Framework for Multimodal Learningcited by 136
  23. 2021End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answeringcited by 133
  24. 2023X-LLM: Bootstrapping Advanced Large Language Models by Treating Multi-Modalities as Foreign Languagescited by 128
  25. 2023WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human Preferencescited by 100
  26. 2024Agent-FLAN: Designing Data and Methods of Effective Agent Tuning for Large Language Modelscited by 100
  27. 2023Improving Language Models via Plug-and-Play Retrieval Feedbackcited by 87
  28. 2021KG-FiD: Infusing Knowledge Graph in Fusion-in-Decoder for Open-Domain Question Answeringcited by 67
  29. 2023UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognitioncited by 64
  30. 2022Few-shot Reranking for Multi-hop QA via Language Model Promptingcited by 19

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 10; 2026: 6.

16 papers.

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  1. 2025MMSearch-R1: Incentivizing LMMs to Searchcited by 124
  2. 2025DeepMMSearch-R1: Empowering Multimodal LLMs in Multimodal Web Searchcited by 42
  3. 2025A Survey on Agentic Multimodal Large Language Modelscited by 23
  4. 2026Towards On-Policy Data Evolution for Visual-Native Multimodal Deep Search Agentscited by 8
  5. 2025ARGUS: Defending Against Multimodal Indirect Prompt Injection via Steering Instruction-Following Behaviorcited by 7
  6. 2026ProMMSearchAgent: A Generalizable Multimodal Search Agent Trained with Process-Oriented Rewardscited by 5
  7. 2025Concept-as-Tree: A Controllable Synthetic Data Framework Makes Stronger Personalized VLMscited by 4
  8. 2025Cache-of-Thought: Master-Apprentice Framework for Cost-Effective Vision Language Model Reasoningcited by 3
  9. 2025Hidden Tail: Adversarial Image Causing Stealthy Resource Consumption in Vision-Language Modelscited by 3
  10. 2026Seeing as Experts Do: A Knowledge-Augmented Agent for Open-Set Fine-Grained Visual Understandingcited by 2
  11. 2025MCiteBench: A Multimodal Benchmark for Generating Text with Citationscited by 1
  12. 2025Efficient Agent: Optimizing Planning Capability for Multimodal Retrieval Augmented Generationcited by 1
4 more
  1. 2026DR-MMSearchAgent: Deepening Reasoning in Multimodal Search Agentscited by 1
  2. 2026WeAgent-MMSearch: Native Text-Vision Interaction for Multimodal Search Agentscited by 1
  3. 2025Agent-based Condition Monitoring Assistance with Multimodal Industrial Database Retrieval Augmented Generationcited by 0
  4. 2026Neos: Learning to Interleave Search and Visual Reasoningcited by 0

Similar, not cited

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  2. 2026Visual-Seeker: Towards Visual-Native Multimodal Agentic Search via Active Visual Reasoning
  3. 2026Vision-DeepResearch: Incentivizing DeepResearch Capability in Multimodal Large Language Models
  4. 2025Vision-Free Retrieval: Rethinking Multimodal Search with Textual Scene Descriptions
  5. 2026DeepVoyager-VL: Incentivizing Vision-in-the-Loop Search for Long-Horizon Multimodal Agents
  6. 2025mRAG: Elucidating the Design Space of Multi-modal Retrieval-Augmented Generation
  7. 2025V-Agent: An Interactive Video Search System Using Vision-Language Models
  8. 2026WikiSeeker: Rethinking the Role of Vision-Language Models in Knowledge-Based Visual Question Answering