{"total":70,"rows":[{"id":"2306.13549","title":"A Survey on Multimodal Large Language Models","created":"2023-06-23","cited_by_count":909,"area":"mllm"},{"id":"2108.10904","title":"SimVLM: Simple Visual Language Model Pretraining with Weak Supervision","created":"2021-08-24","cited_by_count":647,"area":"mllm"},{"id":"2306.09265","title":"LVLM-eHub: A Comprehensive Evaluation Benchmark for Large Vision-Language Models","created":"2023-06-15","cited_by_count":217,"area":"mllm"},{"id":"2202.10401","title":"Vision-Language Pre-Training with Triple Contrastive Learning","created":"2022-02-21","cited_by_count":212,"area":"mllm"},{"id":"2202.09061","title":"VLP: A Survey on Vision-Language Pre-training","created":"2022-02-18","cited_by_count":159,"area":"mllm"},{"id":"2206.09391","title":"Towards Adversarial Attack on Vision-Language Pre-training Models","created":"2022-06-19","cited_by_count":144,"area":"mllm"},{"id":"2210.09263","title":"Vision-Language Pre-training: Basics, Recent Advances, and Future Trends","created":"2022-10-17","cited_by_count":117,"area":"mllm"},{"id":"2305.10400","title":"What You See is What You Read? Improving Text-Image Alignment Evaluation","created":"2023-05-17","cited_by_count":108,"area":"mllm"},{"id":"2301.02280","title":"Filtering, Distillation, and Hard Negatives for Vision-Language Pre-Training","created":"2023-01-05","cited_by_count":91,"area":"mllm"},{"id":"2502.05206","title":"Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety","created":"2025-02-02","cited_by_count":67,"area":"mllm"},{"id":"2311.01477","title":"FaithScore: Fine-grained Evaluations of Hallucinations in Large Vision-Language Models","created":"2023-11-02","cited_by_count":46,"area":"mllm"},{"id":"2303.02995","title":"HiCLIP: Contrastive Language-Image Pretraining with Hierarchy-aware Attention","created":"2023-03-06","cited_by_count":44,"area":"mllm"},{"id":"2211.11152","title":"You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model","created":"2022-11-21","cited_by_count":43,"area":"mllm"},{"id":"2307.06930","title":"mBLIP: Efficient Bootstrapping of Multilingual Vision-LLMs","created":"2023-07-13","cited_by_count":41,"area":"mllm"},{"id":"2406.05491","title":"One Perturbation is Enough: On Generating Universal Adversarial Perturbations against Vision-Language Pre-training Models","created":"2024-06-08","cited_by_count":40,"area":"mllm"},{"id":"2402.15896","title":"Multimodal Instruction Tuning with Conditional Mixture of LoRA","created":"2024-02-24","cited_by_count":36,"area":"mllm"},{"id":"2405.05524","title":"Universal Adversarial Perturbations for Vision-Language Pre-trained Models","created":"2024-05-09","cited_by_count":31,"area":"mllm"},{"id":"2403.04306","title":"Effectiveness Assessment of Recent Large Vision-Language Models","created":"2024-03-07","cited_by_count":29,"area":"mllm"},{"id":"2408.05767","title":"Reference-free Hallucination Detection for Large Vision-Language Models","created":"2024-08-11","cited_by_count":23,"area":"mllm"},{"id":"2203.09067","title":"UNIMO-2: End-to-End Unified Vision-Language Grounded Learning","created":"2022-03-17","cited_by_count":19,"area":"mllm"},{"id":"2208.13628","title":"Efficient Vision-Language Pretraining with Visual Concepts and Hierarchical Alignment","created":"2022-08-29","cited_by_count":19,"area":"mllm"},{"id":"2405.01474","title":"Understanding Figurative Meaning through Explainable Visual Entailment","created":"2024-05-02","cited_by_count":19,"area":"mllm"},{"id":"2206.07699","title":"Write and Paint: Generative Vision-Language Models are Unified Modal Learners","created":"2022-06-15","cited_by_count":17,"area":"mllm"},{"id":"2304.13923","title":"Retrieval-based Knowledge Augmented Vision Language Pre-training","created":"2023-04-27","cited_by_count":17,"area":"mllm"},{"id":"2308.12636","title":"Exploring Transferability of Multimodal Adversarial Samples for Vision-Language Pre-training Models with Contrastive Learning","created":"2023-08-24","cited_by_count":16,"area":"mllm"},{"id":"2409.15657","title":"M$^2$PT: Multimodal Prompt Tuning for Zero-shot Instruction Learning","created":"2024-09-24","cited_by_count":16,"area":"mllm"},{"id":"2403.14401","title":"Pensieve: Retrospect-then-Compare Mitigates Visual Hallucination","created":"2024-03-21","cited_by_count":14,"area":"mllm"},{"id":"2201.12596","title":"MVPTR: Multi-Level Semantic Alignment for Vision-Language Pre-Training via Multi-Stage Learning","created":"2022-01-29","cited_by_count":13,"area":"mllm"},{"id":"2310.02569","title":"ReForm-Eval: Evaluating Large Vision Language Models via Unified Re-Formulation of Task-Oriented Benchmarks","created":"2023-10-04","cited_by_count":12,"area":"mllm"},{"id":"2402.17304","title":"Probing Multimodal Large Language Models for Global and Local Semantic Representations","created":"2024-02-27","cited_by_count":12,"area":"mllm"},{"id":"2411.05254","title":"Hierarchical Visual Feature Aggregation for OCR-Free Document Understanding","created":"2024-11-08","cited_by_count":12,"area":"mllm"},{"id":"2208.09374","title":"VLMAE: Vision-Language Masked Autoencoder","created":"2022-08-19","cited_by_count":11,"area":"mllm"},{"id":"2312.06112","title":"MAFA: Managing False Negatives for Vision-Language Pre-training","created":"2023-12-11","cited_by_count":11,"area":"mllm"},{"id":"2504.05457","title":"Taxonomy-Aware Evaluation of Vision-Language Models","created":"2025-04-07","cited_by_count":11,"area":"mllm"},{"id":"2211.15398","title":"Leveraging per Image-Token Consistency for Vision-Language Pre-training","created":"2022-11-20","cited_by_count":9,"area":"mllm"},{"id":"2503.00723","title":"Re-Imagining Multimodal Instruction Tuning: A Representation View","created":"2025-03-02","cited_by_count":9,"area":"mllm"},{"id":"2207.11401","title":"Chunk-aware Alignment and Lexical Constraint for Visual Entailment with Natural Language Explanations","created":"2022-07-23","cited_by_count":8,"area":"mllm"},{"id":"2209.15270","title":"ERNIE-ViL 2.0: Multi-view Contrastive Learning for Image-Text Pre-training","created":"2022-09-30","cited_by_count":8,"area":"mllm"},{"id":"2305.14676","title":"GRILL: Grounded Vision-language Pre-training via Aligning Text and Image Regions","created":"2023-05-24","cited_by_count":8,"area":"mllm"},{"id":"2407.01081","title":"CVLUE: A New Benchmark Dataset for Chinese Vision-Language Understanding Evaluation","created":"2024-07-01","cited_by_count":8,"area":"mllm"},{"id":"2112.05587","title":"Unified Multimodal Pre-training and Prompt-based Tuning for Vision-Language Understanding and Generation","created":"2021-12-10","cited_by_count":7,"area":"mllm"},{"id":"2211.04861","title":"ERNIE-UniX2: A Unified Cross-lingual Cross-modal Framework for Understanding and Generation","created":"2022-11-09","cited_by_count":7,"area":"mllm"},{"id":"2305.15033","title":"SmartTrim: Adaptive Tokens and Attention Pruning for Efficient Vision-Language Models","created":"2023-05-24","cited_by_count":7,"area":"mllm"},{"id":"2306.00931","title":"\"Let's not Quote out of Context\": Unified Vision-Language Pretraining for Context Assisted Image Captioning","created":"2023-06-01","cited_by_count":7,"area":"mllm"},{"id":"2407.07840","title":"Decompose and Compare Consistency: Measuring VLMs' Answer Reliability via Task-Decomposition Consistency Comparison","created":"2024-07-10","cited_by_count":7,"area":"mllm"},{"id":"2210.13591","title":"Learning by Hallucinating: Vision-Language Pre-training with Weak Supervision","created":"2022-10-24","cited_by_count":6,"area":"mllm"},{"id":"2308.16689","title":"ViLTA: Enhancing Vision-Language Pre-training through Textual Augmentation","created":"2023-08-31","cited_by_count":6,"area":"mllm"},{"id":"2410.02613","title":"NL-Eye: Abductive NLI for Images","created":"2024-10-03","cited_by_count":5,"area":"mllm"},{"id":"2407.17797","title":"A Unified Understanding of Adversarial Vulnerability Regarding Unimodal Models and Vision-Language Pre-training Models","created":"2024-07-25","cited_by_count":4,"area":"mllm"},{"id":"2410.11639","title":"Efficient and Effective Universal Adversarial Attack against Vision-Language Pre-training Models","created":"2024-10-15","cited_by_count":4,"area":"mllm"},{"id":"2212.04267","title":"Vision and Structured-Language Pretraining for Cross-Modal Food Retrieval","created":"2022-12-08","cited_by_count":3,"area":"mllm"},{"id":"2305.07019","title":"Musketeer: Joint Training for Multi-task Vision Language Model with Task Explanation Prompts","created":"2023-05-11","cited_by_count":3,"area":"mllm"},{"id":"2402.13561","title":"Cognitive Visual-Language Mapper: Advancing Multimodal Comprehension with Enhanced Visual Knowledge Alignment","created":"2024-02-21","cited_by_count":3,"area":"mllm"},{"id":"2501.05122","title":"Centurio: On Drivers of Multilingual Ability of Large Vision-Language Model","created":"2025-01-09","cited_by_count":3,"area":"mllm"},{"id":"2511.21717","title":"CrossCheck-Bench: Diagnosing Compositional Failures in Multimodal Conflict Resolution","created":"2025-11-19","cited_by_count":3,"area":"mllm"},{"id":"2303.16133","title":"Exposing and Addressing Cross-Task Inconsistency in Unified Vision-Language Models","created":"2023-03-28","cited_by_count":2,"area":"mllm"},{"id":"2412.13333","title":"Beyond Accuracy: On the Effects of Fine-tuning Towards Vision-Language Model's Prediction Rationality","created":"2024-12-17","cited_by_count":2,"area":"mllm"},{"id":"2508.04469","title":"FrEVL: Leveraging Frozen Pretrained Embeddings for Efficient Vision-Language Understanding","created":"2025-08-06","cited_by_count":2,"area":"mllm"},{"id":"2312.10613","title":"p-Laplacian Adaptation for Generative Pre-trained Vision-Language Models","created":"2023-12-17","cited_by_count":1,"area":"mllm"},{"id":"2509.22123","title":"Multilingual Vision-Language Models, A Survey","created":"2025-09-26","cited_by_count":1,"area":"mllm"},{"id":"2208.00475","title":"Augmenting Vision Language Pretraining by Learning Codebook with Visual Semantics","created":"2022-07-31","cited_by_count":0,"area":"mllm"},{"id":"2407.12498","title":"Evaluating Linguistic Capabilities of Multimodal LLMs in the Lens of Few-Shot Learning","created":"2024-07-17","cited_by_count":0,"area":"mllm"},{"id":"2410.04884","title":"Patch is Enough: Naturalistic Adversarial Patch against Vision-Language Pre-training Models","created":"2024-10-07","cited_by_count":0,"area":"mllm"},{"id":"2410.12595","title":"CMAL: A Novel Cross-Modal Associative Learning Framework for Vision-Language Pre-Training","created":"2024-10-16","cited_by_count":0,"area":"mllm"},{"id":"2511.01831","title":"Routing-Based Continual Learning for Multimodal Large Language Models","created":"2025-11-03","cited_by_count":0,"area":"mllm"},{"id":"2601.10313","title":"Hierarchical Refinement of Universal Multimodal Attacks on Vision-Language Models","created":"2026-01-15","cited_by_count":0,"area":"mllm"},{"id":"2602.13376","title":"An Online Reference-Free Evaluation Framework for Flowchart Image-to-Code Generation","created":"2026-02-13","cited_by_count":0,"area":"mllm"},{"id":"2604.18452","title":"ESsEN: Training Compact Discriminative Vision-Language Transformers in a Low-Resource Setting","created":"2026-04-20","cited_by_count":0,"area":"mllm"},{"id":"2607.14974","title":"On Success and Simplicity: A Second Look at Transferable Vision-Language Attack Pipeline","created":"2026-07-16","cited_by_count":0,"area":"mllm"},{"id":"2607.28991","title":"CAER: Conflict-Aware Evidence Routing with Dual Prefix Experts for Multimodal Large Language Models","created":"2026-07-31","cited_by_count":0,"area":"mllm"}],"next_cursor":null}