mlsanityData to 14 Oct 2026

Universal Vision-Language Dense Retrieval: Learning A Unified Representation Space for Multi-Modal Retrieval

arXiv 2209.00179 ↗First posted 1 Sep 2022cs.IRcited by 58

Not on the map. Why?

Abstract (arXiv)

This paper presents Universal Vision-Language Dense Retrieval (UniVL-DR), which builds a unified model for multi-modal retrieval. UniVL-DR encodes queries and multi-modality resources in an embedding space for searching candidates from different modalities. To learn a unified embedding space for multi-modal retrieval, UniVL-DR proposes two techniques: 1) Universal embedding optimization strategy, which contrastively optimizes the embedding space using the modality-balanced hard negatives; 2) Image verbalization method, which bridges the modality gap between images and texts in the raw data space. UniVL-DR achieves the state-of-the-art on the multi-modal open-domain question answering benchmark, WebQA, and outperforms all retrieval models on the two subtasks, text-text retrieval and text-image retrieval. It demonstrates that universal multi-modal search is feasible to replace the divide-and-conquer pipeline with a united model and also benefits single/cross modality tasks. All source codes of this work are available at https://github.com/OpenMatch/UniVL-DR.

Key facts. Cited by 58 papers in the map (data through 14 Oct 2026). First posted on arXiv 1 Sep 2022.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 11; 2025: 32; 2026: 13.

58 papers.

Sort:

By area:

  1. 2024GME: Improving Universal Multimodal Retrieval by Multimodal LLMscited by 170
  2. 2023UniIR: Training and Benchmarking Universal Multimodal Information Retrieverscited by 166
  3. 2024MM-Embed: Universal Multimodal Retrieval with Multimodal LLMscited by 161
  4. 2024E5-V: Universal Embeddings with Multimodal Large Language Modelscited by 126
  5. 2024MegaPairs: Massive Data Synthesis For Universal Multimodal Retrievalcited by 84
  6. 2024VISTA: Visualized Text Embedding For Universal Multi-Modal Retrievalcited by 67
  7. 2024UniBind: LLM-Augmented Unified and Balanced Representation Space to Bind Them Allcited by 49
  8. 2025mmE5: Improving Multimodal Multilingual Embeddings via High-quality Synthetic Datacited by 49
  9. 2025Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generationcited by 42
  10. 2025A Survey of Multimodal Retrieval-Augmented Generationcited by 37
  11. 2025Analyzing and Boosting the Power of Fine-Grained Visual Recognition for Multi-modal Large Language Modelscited by 31
  12. 2024OmniBind: Teach to Build Unequal-Scale Modality Interaction for Omni-Bind of Allcited by 20
38 more
  1. 2025RealRAG: Retrieval-augmented Realistic Image Generation via Self-reflective Contrastive Learningcited by 20
  2. 2025WavRAG: Audio-Integrated Retrieval Augmented Generation for Spoken Dialogue Modelscited by 18
  3. 2024Cross-modal Retrieval for Knowledge-based Visual Question Answeringcited by 13
  4. 2025Benchmarking Retrieval-Augmented Generation in Multi-Modal Contextscited by 12
  5. 2023MoqaGPT : Zero-Shot Multi-modal Open-domain Question Answering with Large Language Modelcited by 10
  6. 2025U-MARVEL: Unveiling Key Factors for Universal Multimodal Retrieval via Embedding Learning with MLLMscited by 10
  7. 2025UniECS: Unified Multimodal E-Commerce Search Framework with Gated Cross-modal Fusioncited by 10
  8. 2024Image Anything: Towards Reasoning-coherent and Training-free Multi-modal Image Generationcited by 9
  9. 2025See-Saw Modality Balance: See Gradient, and Sew Impaired Vision-Language Balance to Mitigate Dominant Modality Biascited by 9
  10. 2024Synthetic Multimodal Question Generationcited by 8
  11. 2025HIPPO: Enhancing the Table Understanding Capability of LLMs through Hybrid-Modal Preference Optimizationcited by 6
  12. 2025Joint Fusion and Encoding: Advancing Multimodal Retrieval from the Ground Upcited by 6
  13. 2025Supervised Fine-Tuning or Contrastive Learning? Towards Better Multimodal LLM Rerankingcited by 6
  14. 2024Building A Coding Assistant via the Retrieval-Augmented Language Modelcited by 5
  15. 2025Availability-aware Sensor Fusion via Unified Canonical Spacecited by 5
  16. 2025GENIUS: A Generative Framework for Universal Multimodal Searchcited by 5
  17. 2025ChartCards: A Chart-Metadata Generation Framework for Multi-Task Chart Understandingcited by 5
  18. 2025From Generator to Embedder: Harnessing Innate Abilities of Multimodal LLMs via Building Zero-Shot Discriminative Embedding Modelcited by 5
  19. 2025OmniBridge: Unified Multimodal Understanding, Generation, and Retrieval via Latent Space Alignmentcited by 5
  20. 2025FuseLIP: Multimodal Embeddings via Early Fusion of Discrete Tokenscited by 3
  21. 2025MAVIS: A Benchmark for Multimodal Source Attribution in Long-form Visual Question Answeringcited by 3
  22. 2025Towards Text-Image Interleaved Retrievalcited by 2
  23. 2025Quantifying Memorization and Parametric Response Rates in Retrieval-Augmented Vision-Language Modelscited by 2
  24. 2025RA-Touch: Retrieval-Augmented Touch Understanding with Enriched Visual Datacited by 2
  25. 2025MrM: Black-Box Membership Inference Attacks against Multimodal RAG Systemscited by 2
  26. 2025MCA: Modality Composition Awareness for Robust Composed Multimodal Retrievalcited by 2
  27. 2025Generative Giants, Retrieval Weaklings: Why do Multimodal Large Language Models Fail at Multimodal Retrieval?cited by 2
  28. 2026V-Retrver: Evidence-Driven Agentic Reasoning for Universal Multimodal Retrievalcited by 2
  29. 2026Pailitao-VL: Unified Embedding and Reranker for Real-Time Multi-Modal Industrial Searchcited by 2
  30. 2026Beyond Global Similarity: Towards Fine-Grained, Multi-Condition Multimodal Retrievalcited by 2
  31. 2025Boosting Text-to-Chart Retrieval through Training with Synthesized Semantic Insightscited by 1
  32. 2025Bridging the Modality Gap by Similarity Standardization with Pseudo-Positive Samplescited by 1
  33. 2026Enhancing Multimodal Retrieval via Complementary Information Extraction and Alignmentcited by 1
  34. 2026Spectral Disentanglement and Enhancement: A Dual-domain Contrastive Framework for Representation Learningcited by 1
  35. 2026From Scenes to Elements: Multi-Granularity Evidence Retrieval for Verifiable Multimodal RAGcited by 1
  36. 2025Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gapcited by 0
  37. 2025F2RVLM: Boosting Fine-grained Fragment Retrieval for Multi-Modal Long-form Dialogue with Vision Language Modelcited by 0
  38. 2025FANoise: Singular Value-Adaptive Noise Modulation for Robust Multimodal Representation Learningcited by 0

50 most cited of 58 All 58 (JSON)