{"total":25,"rows":[{"id":"2404.07177","title":"Scaling Laws for Data Filtering -- Data Curation cannot be Compute Agnostic","created":"2024-04-10","cited_by_count":77,"area":"mllm"},{"id":"2310.07699","title":"VeCLIP: Improving CLIP Training via Visual-enriched Captions","created":"2023-10-11","cited_by_count":70,"area":"mllm"},{"id":"2310.02110","title":"Sieve: Multimodal Dataset Pruning Using Image Captioning Models","created":"2023-10-03","cited_by_count":33,"area":"mllm"},{"id":"2403.19137","title":"CLAP4CLIP: Continual Learning with Probabilistic Finetuning for Vision-Language Models","created":"2024-03-28","cited_by_count":25,"area":"mllm"},{"id":"2409.17958","title":"The Hard Positive Truth about Vision-Language Compositionality","created":"2024-09-26","cited_by_count":22,"area":"mllm"},{"id":"2305.08675","title":"Improved baselines for vision-language pre-training","created":"2023-05-15","cited_by_count":20,"area":"mllm"},{"id":"2405.19547","title":"CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning","created":"2024-05-29","cited_by_count":20,"area":"mllm"},{"id":"2508.04227","title":"Continual Learning for VLMs: A Survey and Taxonomy Beyond Forgetting","created":"2025-08-06","cited_by_count":18,"area":"mllm"},{"id":"2404.02145","title":"Iterated Learning Improves Compositionality in Large Vision-Language Models","created":"2024-04-02","cited_by_count":17,"area":"mllm"},{"id":"2410.18857","title":"Probabilistic Language-Image Pre-Training","created":"2024-10-24","cited_by_count":16,"area":"mllm"},{"id":"2304.11619","title":"SATIN: A Multi-Task Metadataset for Classifying Satellite Imagery using Vision-Language Models","created":"2023-04-23","cited_by_count":15,"area":"mllm"},{"id":"2302.06891","title":"UKnow: A Unified Knowledge Protocol with Multimodal Knowledge Graph Datasets for Reasoning and Vision-Language Pre-Training","created":"2023-02-14","cited_by_count":14,"area":"mllm"},{"id":"2401.14555","title":"Revisiting Active Learning in the Era of Vision Foundation Models","created":"2024-01-25","cited_by_count":14,"area":"mllm"},{"id":"2306.08893","title":"LOVM: Language-Only Vision Model Selection","created":"2023-06-15","cited_by_count":12,"area":"mllm"},{"id":"2305.16999","title":"Three Towers: Flexible Contrastive Learning with Pretrained Image Models","created":"2023-05-26","cited_by_count":11,"area":"mllm"},{"id":"2507.22431","title":"HQ-CLIP: Leveraging Large Vision-Language Models to Create High-Quality Image-Text Datasets and CLIP Models","created":"2025-07-30","cited_by_count":11,"area":"mllm"},{"id":"2402.02055","title":"Variance Alignment Score: A Simple But Tough-to-Beat Data Selection Method for Multimodal Contrastive Learning","created":"2024-02-03","cited_by_count":6,"area":"mllm"},{"id":"2501.18271","title":"Vision-Language Model Selection and Reuse for Downstream Adaptation","created":"2025-01-30","cited_by_count":3,"area":"mllm"},{"id":"2408.13979","title":"Nemesis: Normalizing the Soft-prompt Vectors of Vision-Language Models","created":"2024-08-26","cited_by_count":2,"area":"mllm"},{"id":"2503.08048","title":"LongProLIP: A Probabilistic Vision-Language Model with Long Context Text","created":"2025-03-11","cited_by_count":1,"area":"mllm"},{"id":"2405.03190","title":"Adapting Dual-encoder Vision-language Models for Paraphrased Retrieval","created":"2024-05-06","cited_by_count":0,"area":"mllm"},{"id":"2602.01346","title":"Model Specific Task Similarity for Vision Language Model Selection via Layer Conductance","created":"2026-02-01","cited_by_count":0,"area":"mllm"},{"id":"2603.11211","title":"A Simple Efficiency Incremental Learning Framework via Vision-Language Model with Nonlinear Multi-Adapters","created":"2026-03-11","cited_by_count":0,"area":"mllm"},{"id":"2603.21077","title":"CoVFT: Context-aware Visual Fine-tuning for Multimodal Large Language Models","created":"2026-03-22","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"}],"next_cursor":null}