{"total":126,"rows":[{"id":"2601.04720","title":"Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking","created":"2026-01-08","cited_by_count":230,"area":null},{"id":"2509.20354","title":"EmbeddingGemma: Powerful and Lightweight Text Representations","created":"2025-09-24","cited_by_count":139,"area":null},{"id":"2507.04590","title":"VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents","created":"2025-07-07","cited_by_count":116,"area":null},{"id":"2503.07891","title":"Gemini Embedding: Generalizable Embeddings from Gemini","created":"2025-03-10","cited_by_count":94,"area":null},{"id":"2510.13515","title":"UniME-V2: MLLM-as-a-Judge for Universal Multimodal Embedding Learning","created":"2025-10-15","cited_by_count":42,"area":null},{"id":"2509.18095","title":"MetaEmbed: Scaling Multimodal Retrieval at Test-Time with Flexible Late Interaction","created":"2025-09-22","cited_by_count":39,"area":null},{"id":"2505.11293","title":"Breaking the Batch Barrier (B3) of Contrastive Learning via Smart Batch Mining","created":"2025-05-16","cited_by_count":28,"area":null},{"id":"2505.19650","title":"Modality Curation: Building Universal Embeddings for Advanced Multimodal Information Retrieval","created":"2025-05-26","cited_by_count":26,"area":null},{"id":"2509.23883","title":"DocPruner: A Storage-Efficient Framework for Multi-Vector Visual Document Retrieval via Adaptive Patch-Level Embedding Pruning","created":"2025-09-28","cited_by_count":20,"area":null},{"id":"2504.10471","title":"MIEB: Massive Image Embedding Benchmark","created":"2025-04-14","cited_by_count":15,"area":null},{"id":"2601.03666","title":"e5-omni: Explicit Cross-modal Alignment for Omni-modal Embeddings","created":"2026-01-07","cited_by_count":13,"area":null},{"id":"2507.19054","title":"Closing the Modality Gap for Mixed Modality Search","created":"2025-07-25","cited_by_count":12,"area":null},{"id":"2411.04997","title":"LLM2CLIP: Powerful Language Model Unlocks Richer Cross-Modality Representation","created":"2024-11-07","cited_by_count":11,"area":null},{"id":"2507.14902","title":"U-MARVEL: Unveiling Key Factors for Universal Multimodal Retrieval via Embedding Learning with MLLMs","created":"2025-07-20","cited_by_count":10,"area":null},{"id":"2510.12709","title":"SAIL-Embedding Technical Report: Omni-modal Embedding Foundation Model","created":"2025-10-14","cited_by_count":10,"area":null},{"id":"2602.19549","title":"Sculpting the Vector Space: Towards Efficient Multi-Vector Visual Document Retrieval via Prune-then-Merge Framework","created":"2026-02-23","cited_by_count":10,"area":null},{"id":"2602.21202","title":"Multi-Vector Index Compression in Any Modality","created":"2026-02-24","cited_by_count":10,"area":null},{"id":"2506.06144","title":"CLaMR: Contextualized Late-Interaction for Multimodal Content Retrieval","created":"2025-06-06","cited_by_count":9,"area":null},{"id":"2502.11431","title":"Any Information Is Just Worth One Single Screenshot: Unifying Search With Visualized Information Retrieval","created":"2025-02-17","cited_by_count":8,"area":null},{"id":"2504.00954","title":"IDMR: Towards Instance-Driven Precise Visual Correspondence in Multimodal Retrieval","created":"2025-04-01","cited_by_count":8,"area":null},{"id":"2511.19278","title":"ReMatch: Boosting Representation through Matching for Multimodal Retrieval","created":"2025-11-24","cited_by_count":8,"area":null},{"id":"2602.19961","title":"Unlocking Multimodal Document Intelligence: From Current Triumphs to Future Frontiers of Visual Document Retrieval","created":"2026-02-23","cited_by_count":8,"area":null},{"id":"2604.10167","title":"Visual Late Chunking: An Empirical Study of Contextual Chunking for Efficient Visual Document Retrieval","created":"2026-04-11","cited_by_count":8,"area":null},{"id":"2608.24053","title":"WeMM-Embedding: WeChat Multi-Modal Embedding Technical Report","created":"2026-08-25","cited_by_count":8,"area":null},{"id":"2503.09402","title":"VLog: Video-Language Models by Generative Retrieval of Narration Vocabulary","created":"2025-03-12","cited_by_count":7,"area":null},{"id":"2509.25638","title":"Generalized Contrastive Learning for Universal Multimodal Retrieval","created":"2025-09-30","cited_by_count":7,"area":null},{"id":"2509.26378","title":"MR$^2$-Bench: Going Beyond Matching to Reasoning in Multimodal Retrieval","created":"2025-09-30","cited_by_count":7,"area":null},{"id":"2603.12572","title":"LMEB: Long-horizon Memory Embedding Benchmark","created":"2026-03-13","cited_by_count":7,"area":null},{"id":"2502.20008","title":"Joint Fusion and Encoding: Advancing Multimodal Retrieval from the Ground Up","created":"2025-02-27","cited_by_count":6,"area":null},{"id":"2508.12149","title":"MOVER: Multimodal Optimal Transport with Volume-based Embedding Regularization","created":"2025-08-16","cited_by_count":6,"area":null},{"id":"2505.15877","title":"Highlighting What Matters: Promptable Embeddings for Attribute-Focused Image Retrieval","created":"2025-05-21","cited_by_count":5,"area":null},{"id":"2510.06888","title":"M3Retrieve: Benchmarking Multimodal Retrieval for Medicine","created":"2025-10-08","cited_by_count":5,"area":null},{"id":"2604.02045","title":"BidirLM: From Text to Omnimodal Bidirectional Encoders by Adapting and Composing Causal LLMs","created":"2026-04-02","cited_by_count":5,"area":null},{"id":"2504.08368","title":"FocalLens: Instruction Tuning Enables Zero-Shot Conditional Image Representations","created":"2025-04-11","cited_by_count":4,"area":null},{"id":"2511.04910","title":"SDS KoPub VDR: A Benchmark Dataset for Visual Document Retrieval in Korean Public Documents","created":"2025-11-07","cited_by_count":4,"area":null},{"id":"2601.12193","title":"VeRVE: Versatile Retrieval for Videos via Unified Embeddings","created":"2026-01-17","cited_by_count":4,"area":null},{"id":"2603.01666","title":"Beyond the Grid: Layout-Informed Multi-Vector Retrieval with Parsed Visual Document Representations","created":"2026-03-02","cited_by_count":4,"area":null},{"id":"2506.03096","title":"FuseLIP: Multimodal Embeddings via Early Fusion of Discrete Tokens","created":"2025-06-03","cited_by_count":3,"area":null},{"id":"2506.16552","title":"Revela: Dense Retriever Learning via Language Modeling","created":"2025-06-19","cited_by_count":3,"area":null},{"id":"2506.22056","title":"Universal Retrieval for Multimodal Trajectory Modeling","created":"2025-06-27","cited_by_count":3,"area":null},{"id":"2507.20783","title":"On The Role of Pretrained Language Models in General-Purpose Text Embeddings: A Survey","created":"2025-07-28","cited_by_count":3,"area":null},{"id":"2511.01588","title":"Explore More, Learn Better: Parallel MLLM Embeddings under Mutual Information Minimization","created":"2025-11-03","cited_by_count":3,"area":null},{"id":"2511.13189","title":"Large Language Models Meet Extreme Multi-label Classification: Scaling and Multi-modal Framework","created":"2025-11-17","cited_by_count":3,"area":null},{"id":"2511.13415","title":"Attention Grounded Enhancement for Visual Document Retrieval","created":"2025-11-17","cited_by_count":3,"area":null},{"id":"2512.03514","title":"M3DR: Towards Universal Multilingual Multimodal Document Retrieval","created":"2025-12-03","cited_by_count":3,"area":null},{"id":"2602.05729","title":"Adaptive Global and Fine-Grained Perceptual Fusion for MLLM Embeddings Compatible with Hard Negative Amplification","created":"2026-02-05","cited_by_count":3,"area":null},{"id":"2602.09839","title":"ARK: A Dual-Axis Multimodal Retrieval Benchmark along Reasoning and Knowledge","created":"2026-02-10","cited_by_count":3,"area":null},{"id":"2602.22278","title":"RETLLM: Training and Data-Free MLLMs for Multimodal Information Retrieval","created":"2026-02-25","cited_by_count":3,"area":null},{"id":"2603.02098","title":"Efficient and High-Fidelity Omni Modality Retrieval","created":"2026-03-02","cited_by_count":3,"area":null},{"id":"2607.18237","title":"The Many Senses of Visual Similarity: A Text-Prompted Image Perceptual Metric","created":"2026-07-20","cited_by_count":3,"area":null},{"id":"2607.18666","title":"Fusion Embedding: A Unified Embedding Space for Text, Image, Video, and Audio","created":"2026-07-21","cited_by_count":3,"area":null},{"id":"2502.07221","title":"Histopathology Multi-modal Embedding for Pathology Composed Retrieval","created":"2025-02-11","cited_by_count":2,"area":null},{"id":"2510.15543","title":"MCA: Modality Composition Awareness for Robust Composed Multimodal Retrieval","created":"2025-10-17","cited_by_count":2,"area":null},{"id":"2511.02358","title":"Let Multimodal Embedders Learn When to Augment Query via Adaptive Query Augmentation","created":"2025-11-04","cited_by_count":2,"area":null},{"id":"2602.13704","title":"Pailitao-VL: Unified Embedding and Reranker for Real-Time Multi-Modal Industrial Search","created":"2026-02-14","cited_by_count":2,"area":null},{"id":"2603.01493","title":"PhotoBench: Beyond Visual Matching Towards Personalized Intent-Driven Photo Retrieval","created":"2026-03-02","cited_by_count":2,"area":null},{"id":"2605.06460","title":"MINER: Mining Multimodal Internal Representation for Efficient Retrieval","created":"2026-05-07","cited_by_count":2,"area":null},{"id":"2608.02148","title":"Douyin Multimodal Embedding Model Technical Report","created":"2026-08-03","cited_by_count":2,"area":null},{"id":"2503.00329","title":"ABC: Achieving Better Control of Multimodal Embeddings using VLMs","created":"2025-03-01","cited_by_count":1,"area":null},{"id":"2505.21459","title":"LazyVLM: Neuro-Symbolic Approach to Video Analytics","created":"2025-05-27","cited_by_count":1,"area":null},{"id":"2508.17497","title":"Multimodal Representation Learning Conditioned on Semantic Relations","created":"2025-08-24","cited_by_count":1,"area":null},{"id":"2601.16125","title":"Rethinking Composed Image Retrieval Evaluation: A Fine-Grained Benchmark from Image Editing","created":"2026-01-22","cited_by_count":1,"area":null},{"id":"2602.08342","title":"UrbanGraphEmbeddings: Learning and Evaluating Spatially Grounded Multimodal Embeddings for Urban Science","created":"2026-02-09","cited_by_count":1,"area":null},{"id":"2602.09066","title":"Spectral Disentanglement and Enhancement: A Dual-domain Contrastive Framework for Representation Learning","created":"2026-02-09","cited_by_count":1,"area":null},{"id":"2604.10721","title":"Turning Generators into Retrievers: Unlocking MLLMs for Natural Language-Guided Geo-Localization","created":"2026-04-12","cited_by_count":1,"area":null},{"id":"2604.17054","title":"mEOL: Training-Free Instruction-Guided Multimodal Embedder for Vector Graphics and Image Retrieval","created":"2026-04-18","cited_by_count":1,"area":null},{"id":"2605.22552","title":"FashionLens: Toward Versatile Fashion Image Retrieval via Task-Adaptive Learning","created":"2026-05-21","cited_by_count":1,"area":null},{"id":"2605.24938","title":"Your Embedding Model is SMARTer Than You Think","created":"2026-05-24","cited_by_count":1,"area":null},{"id":"2605.26641","title":"OmniRetriever: Any-to-Any Audio-Video-Text Retrieval via Fusion-as-Teacher Distillation","created":"2026-05-26","cited_by_count":1,"area":null},{"id":"2606.14958","title":"MVEB: Massive Video Embedding Benchmark","created":"2026-06-12","cited_by_count":1,"area":null},{"id":"2606.23539","title":"LightSTAR: Efficient Visual Document Retrieval via Lightweight Selection with Vision-Adaptive Refinement","created":"2026-06-22","cited_by_count":1,"area":null},{"id":"2608.01794","title":"Illuminating Visual Identity in Universal Multimodal Embeddings","created":"2026-08-03","cited_by_count":1,"area":null},{"id":"2608.28695","title":"Weaving Visual Narratives: Agentic Image Bundle Composition Beyond Atomic Visual Matching","created":"2026-08-27","cited_by_count":1,"area":null},{"id":"2609.01778","title":"Allocate Before You Embed: Adaptive Visual Input Allocation for Video Embeddings","created":"2026-09-01","cited_by_count":1,"area":null},{"id":"2609.15152","title":"PACE: Progressive Angular-to-Norm Contrastive Embedding","created":"2026-09-14","cited_by_count":1,"area":null},{"id":"2511.20854","title":"Unsupervised Memorability Modeling from Tip-of-the-Tongue Retrieval Queries","created":"2025-11-25","cited_by_count":0,"area":null},{"id":"2511.20997","title":"FANoise: Singular Value-Adaptive Noise Modulation for Robust Multimodal Representation Learning","created":"2025-11-26","cited_by_count":0,"area":null},{"id":"2512.11490","title":"VLM2GeoVec: Toward Universal Multimodal Embeddings for Remote Sensing","created":"2025-12-12","cited_by_count":0,"area":null},{"id":"2512.13511","title":"Adapting MLLMs for Nuanced Video Retrieval","created":"2025-12-15","cited_by_count":0,"area":null},{"id":"2602.01753","title":"ObjEmbed: Towards Universal Multimodal Object Embeddings","created":"2026-02-02","cited_by_count":0,"area":null},{"id":"2603.11520","title":"FBCIR: Balancing Cross-Modal Focuses in Composed Image Retrieval","created":"2026-03-12","cited_by_count":0,"area":null},{"id":"2603.17186","title":"Visual Product Search Benchmark","created":"2026-03-17","cited_by_count":0,"area":null},{"id":"2604.07201","title":"BRIDGE: Multimodal-to-Text Retrieval via Reinforcement-Learned Query Alignment","created":"2026-04-08","cited_by_count":0,"area":null},{"id":"2604.15628","title":"SIMMER: Cross-Modal Food Image--Recipe Retrieval via MLLM-Based Embedding","created":"2026-04-17","cited_by_count":0,"area":null},{"id":"2605.15723","title":"GOMA: Toward Structure-Driven Multimodal Alignment from a Graph Signal Smoothing Perspective","created":"2026-05-15","cited_by_count":0,"area":null},{"id":"2605.15868","title":"SOLAR: Self-supervised Joint Learning for Symmetric Multimodal Retrieval","created":"2026-05-15","cited_by_count":0,"area":null},{"id":"2605.21832","title":"FLUID: From Ephemeral IDs to Multimodal Semantic Codes for Industrial-Scale Livestreaming Recommendation","created":"2026-05-20","cited_by_count":0,"area":null},{"id":"2605.30027","title":"DocRetriever: A Plug-and-Play Framework for Multimodal Document Retrieval with Comprehensive Benchmark","created":"2026-05-28","cited_by_count":0,"area":null},{"id":"2605.30917","title":"Inference-Free Multimodal Learned Sparse Retrieval for Production-Scale Visual Document Search","created":"2026-05-29","cited_by_count":0,"area":null},{"id":"2605.31040","title":"UniRTL: Unifying Code and Graph for Robust RTL Representation Learning","created":"2026-05-29","cited_by_count":0,"area":null},{"id":"2606.01702","title":"KDH-CAD: Knowledge-data hybrid CAD learning under data scarcity","created":"2026-06-01","cited_by_count":0,"area":null},{"id":"2606.03345","title":"Beyond Semantics: Modeling Factual and Affective Perceptual Experiences from Vision-Language Data","created":"2026-06-02","cited_by_count":0,"area":null},{"id":"2606.04591","title":"Fine-grained Fragment Retrieval in Multi-modal Long-form Dialogues","created":"2026-06-03","cited_by_count":0,"area":null},{"id":"2606.09331","title":"Conan-embedding-v3: Fusing Modality-Specific Models for Omni-Modal Embedding","created":"2026-06-08","cited_by_count":0,"area":null},{"id":"2606.12215","title":"MLT-Dedup: Efficient Large-Scale Online Video Deduplication via Multi-Level Representations and Spatial-Temporal Matching","created":"2026-06-10","cited_by_count":0,"area":null},{"id":"2606.12883","title":"The Hidden Power of Scaling Factor in LoRA Optimization","created":"2026-06-11","cited_by_count":0,"area":null},{"id":"2606.14747","title":"MMLongEmbed: Benchmarking Multimodal Embedding Models in Long-Context Scenarios","created":"2026-06-05","cited_by_count":0,"area":null},{"id":"2606.24094","title":"Universal Guideline-Driven Image Clustering via a Hybrid LLM Agent","created":"2026-06-23","cited_by_count":0,"area":null},{"id":"2606.28329","title":"$M^3 QuestionIng$: Multi-modal Multi-span Medical Question Answering","created":"2026-05-19","cited_by_count":0,"area":null},{"id":"2607.05927","title":"CMDR: Contextual Multimodal Document Retrieval","created":"2026-07-07","cited_by_count":0,"area":null}],"next_cursor":"100"}