{"total":57,"rows":[{"id":"2506.01844","title":"SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics","created":"2025-06-02","cited_by_count":530,"area":"mllm"},{"id":"2512.10942","title":"VL-JEPA: Joint Embedding Predictive Architecture for Vision-language","created":"2025-12-11","cited_by_count":68,"area":"mllm"},{"id":"2507.22062","title":"Meta CLIP 2: A Worldwide Scaling Recipe","created":"2025-07-29","cited_by_count":64,"area":"mllm"},{"id":"2510.15042","title":"Comprehensive language-image pre-training for 3D medical image understanding","created":"2025-10-16","cited_by_count":22,"area":"mllm"},{"id":"2604.12012","title":"TIPSv2: Advancing Vision-Language Pretraining with Enhanced Patch-Text Alignment","created":"2026-04-13","cited_by_count":13,"area":"mllm"},{"id":"2603.12254","title":"Attend Before Attention: Efficient and Scalable Video Understanding via Autoregressive Gazing","created":"2026-03-12","cited_by_count":9,"area":"mllm"},{"id":"2601.06843","title":"Speak While Watching: Unleashing TRUE Real-Time Video Understanding Capability of Multimodal Large Language Models","created":"2026-01-11","cited_by_count":8,"area":"mllm"},{"id":"2604.05418","title":"VideoStir: Understanding Long Videos via Spatio-Temporally Structured and Intent-Aware RAG","created":"2026-04-07","cited_by_count":6,"area":"mllm"},{"id":"2604.06912","title":"Q-Zoom: Query-Aware Adaptive Perception for Efficient Multimodal Large Language Models","created":"2026-04-08","cited_by_count":6,"area":"mllm"},{"id":"2512.23592","title":"Same or Not? Enhancing Visual Perception in Vision-Language Models","created":"2025-12-29","cited_by_count":5,"area":"mllm"},{"id":"2507.07104","title":"Vision-Language-Vision Auto-Encoder: Scalable Knowledge Distillation from Diffusion Models","created":"2025-07-09","cited_by_count":4,"area":"mllm"},{"id":"2602.08099","title":"VidVec: Unlocking Video MLLM Embeddings for Video-Text Retrieval","created":"2026-02-08","cited_by_count":4,"area":"mllm"},{"id":"2603.13341","title":"Mind the Discriminability Trap in Source-Free Cross-domain Few-shot Learning","created":"2026-03-07","cited_by_count":4,"area":"mllm"},{"id":"2603.17655","title":"Interpretable Cross-Domain Few-Shot Learning with Rectified Target-Domain Local Alignment","created":"2026-03-18","cited_by_count":4,"area":"mllm"},{"id":"2510.06529","title":"VUGEN: Visual Understanding priors for GENeration","created":"2025-10-08","cited_by_count":3,"area":"mllm"},{"id":"2510.16333","title":"RL makes MLLMs see better than SFT","created":"2025-10-18","cited_by_count":3,"area":"mllm"},{"id":"2603.19862","title":"IsoCLIP: Decomposing CLIP Projectors for Efficient Intra-modal Alignment","created":"2026-03-20","cited_by_count":3,"area":"mllm"},{"id":"2607.24743","title":"ClinFusion: A Vision-Centric Multimodal LLM System for Holistic Medical Understanding","created":"2026-07-27","cited_by_count":3,"area":"mllm"},{"id":"2609.01004","title":"SinkPruner: Sink-Free Visual Token Pruning for Multimodal Large Language Models","created":"2026-09-01","cited_by_count":3,"area":"mllm"},{"id":"2508.20760","title":"Occlusion Robustness of CLIP for Military Vehicle Classification","created":"2025-08-28","cited_by_count":2,"area":"mllm"},{"id":"2510.04547","title":"Activation Quantization of Vision Encoders Needs Prefixing Registers","created":"2025-10-06","cited_by_count":2,"area":"mllm"},{"id":"2512.17221","title":"DAVE: A VLM Vision Encoder for Document Understanding and Web Agents","created":"2025-12-19","cited_by_count":2,"area":"mllm"},{"id":"2601.20075","title":"Sparse CLIP: Co-Optimizing Interpretability and Performance in Contrastive Learning","created":"2026-01-27","cited_by_count":2,"area":"mllm"},{"id":"2603.24528","title":"Cross-Modal Prototype Alignment and Mixing for Training-Free Few-Shot Classification","created":"2026-03-25","cited_by_count":2,"area":"mllm"},{"id":"2604.20318","title":"UniCVR: From Alignment to Reranking for Unified Zero-Shot Composed Visual Retrieval","created":"2026-04-22","cited_by_count":2,"area":"mllm"},{"id":"2605.25799","title":"Addressing Exacerbated Attention Sink for Source-Free Cross-Domain Few-Shot Learning","created":"2026-05-25","cited_by_count":2,"area":"mllm"},{"id":"2509.17374","title":"Revisiting Vision Language Foundations for No-Reference Image Quality Assessment","created":"2025-09-22","cited_by_count":1,"area":"mllm"},{"id":"2510.16290","title":"Cerberus: Real-Time Video Anomaly Detection via Cascaded Vision-Language Models","created":"2025-10-18","cited_by_count":1,"area":"mllm"},{"id":"2510.21849","title":"TowerVision: Understanding and Improving Multilinguality in Vision-Language Models","created":"2025-10-22","cited_by_count":1,"area":"mllm"},{"id":"2510.25682","title":"PairUni: Pairwise Training for Unified Multimodal Language Models","created":"2025-10-29","cited_by_count":1,"area":"mllm"},{"id":"2511.18448","title":"EventBench: Towards Comprehensive Benchmarking of Event-based MLLMs","created":"2025-11-23","cited_by_count":1,"area":"mllm"},{"id":"2511.20770","title":"Text-Guided Semantic Image Encoder","created":"2025-11-25","cited_by_count":1,"area":"mllm"},{"id":"2602.09934","title":"VersaViT: Enhancing MLLM Vision Backbones via Task-Guided Optimization","created":"2026-02-10","cited_by_count":1,"area":"mllm"},{"id":"2602.21406","title":"Exploring Vision-Language Models for Open-Vocabulary Zero-Shot Action Segmentation","created":"2026-02-24","cited_by_count":1,"area":"mllm"},{"id":"2604.11496","title":"Revisiting Compositionality in Dual-Encoder Vision-Language Models: The Role of Inference","created":"2026-04-13","cited_by_count":1,"area":"mllm"},{"id":"2605.29776","title":"Improving CLIP Adaptation by Breaking Tail Alignment for Source-Free Cross-Domain Few-Shot Learning","created":"2026-05-28","cited_by_count":1,"area":"mllm"},{"id":"2606.11188","title":"ARM: An AutoRegressive Large Multimodal Model with Unified Discrete Representations","created":"2026-06-09","cited_by_count":1,"area":"mllm"},{"id":"2608.17402","title":"MoE-ViE: Mixture of Experts Vision Encoder for Efficient Image and Video Understanding","created":"2026-08-18","cited_by_count":1,"area":"mllm"},{"id":"2507.04735","title":"An analysis of vision-language models for fabric retrieval","created":"2025-07-07","cited_by_count":0,"area":"mllm"},{"id":"2602.13961","title":"MarsRetrieval: Benchmarking Vision-Language Models for Planetary-Scale Geospatial Retrieval on Mars","created":"2026-02-15","cited_by_count":0,"area":"mllm"},{"id":"2603.01096","title":"Unified Vision-Language Modeling via Concept Space Alignment","created":"2026-03-01","cited_by_count":0,"area":"mllm"},{"id":"2603.03544","title":"PinCLIP: Large-scale Foundational Multimodal Representation at Pinterest","created":"2026-03-03","cited_by_count":0,"area":"mllm"},{"id":"2603.24804","title":"GoldiCLIP: The Goldilocks Approach for Balancing Explicit Supervision for Language-Image Pretraining","created":"2026-03-25","cited_by_count":0,"area":"mllm"},{"id":"2604.12551","title":"Cross-Attentive Multiview Fusion of Vision-Language Embeddings","created":"2026-04-14","cited_by_count":0,"area":"mllm"},{"id":"2604.13313","title":"Concrete Jungle: Towards Concreteness Paved Contrastive Negative Mining for Compositional Understanding","created":"2026-04-14","cited_by_count":0,"area":"mllm"},{"id":"2605.18029","title":"What Matters for Grocery Product Retrieval with Open Source Vision Language Models","created":"2026-05-18","cited_by_count":0,"area":"mllm"},{"id":"2605.19130","title":"EgoBabyVLM: Benchmarking Cross-Modal Learning from Naturalistic Egocentric Video Data","created":"2026-05-18","cited_by_count":0,"area":"mllm"},{"id":"2606.04433","title":"Stateful Visual Encoders for Vision-Language Models","created":"2026-06-03","cited_by_count":0,"area":"mllm"},{"id":"2606.08126","title":"One Stone, Three Birds: Self-adaptive Optimal Transport for Multi-VLM Selection, Adaptation, and Ensembling","created":"2026-06-06","cited_by_count":0,"area":"mllm"},{"id":"2606.11200","title":"Detecting AI-Generated Content on Social Media with Multi-modal Language Models","created":"2026-04-21","cited_by_count":0,"area":"mllm"},{"id":"2607.23373","title":"UltraViT: Latency-Optimized On-device Vision Encoder for Large Vision-Language Models","created":"2026-07-25","cited_by_count":0,"area":"mllm"},{"id":"2607.28211","title":"Scaling Vision-Language Models Is Not Enough to Mitigate Bias","created":"2026-07-30","cited_by_count":0,"area":"mllm"},{"id":"2607.28627","title":"ReToken: One Token to Improve Vision-Language Models for Visual Retrieval","created":"2026-07-30","cited_by_count":0,"area":"mllm"},{"id":"2608.08904","title":"From Recovery to Drop-off: How Action Post-training Reduces a VLM's Late-Layer Depth Decodability","created":"2026-08-09","cited_by_count":0,"area":"mllm"},{"id":"2609.06360","title":"NOVA: Normal-Side Modeling for Training-Free Zero-Shot Video Anomaly Detection","created":"2026-09-06","cited_by_count":0,"area":"mllm"},{"id":"2610.05413","title":"A Strong Baseline for Evaluating Vision Encoders in Multimodal Large Language Models","created":"2026-10-04","cited_by_count":0,"area":"mllm"},{"id":"2610.17866","title":"MicroCLIP: Connecting Text and Microscopy Images via Contrastive Language--Image Pretraining","created":"2026-10-13","cited_by_count":0,"area":"mllm"}],"next_cursor":null}