{"total":25,"rows":[{"id":"2303.02151","title":"Prompt, Generate, then Cache: Cascade of Foundation Models makes Strong Few-shot Learners","created":"2023-03-03","cited_by_count":152,"area":null},{"id":"2209.14169","title":"CALIP: Zero-Shot Enhancement of CLIP with Parameter-free Attention","created":"2022-09-28","cited_by_count":103,"area":null},{"id":"2401.18084","title":"Binding Touch to Everything: Learning Unified Multimodal Tactile Representations","created":"2024-01-31","cited_by_count":95,"area":null},{"id":"2304.01195","title":"Not All Features Matter: Enhancing Few-shot CLIP with Adaptive Prior Refinement","created":"2023-04-03","cited_by_count":84,"area":null},{"id":"2411.17040","title":"Multimodal Alignment and Fusion: A Survey","created":"2024-11-26","cited_by_count":74,"area":null},{"id":"2303.16894","title":"ViewRefer: Grasp the Multi-view Knowledge for 3D Visual Grounding with GPT and Prototype Guidance","created":"2023-03-29","cited_by_count":70,"area":null},{"id":"2207.01077","title":"Can Language Understand Depth?","created":"2022-07-03","cited_by_count":69,"area":null},{"id":"2302.14007","title":"Joint-MAE: 2D-3D Joint Masked Autoencoders for 3D Point Cloud Pre-training","created":"2023-02-27","cited_by_count":52,"area":null},{"id":"2404.03635","title":"WorDepth: Variational Language Prior for Monocular Depth Estimation","created":"2024-04-04","cited_by_count":34,"area":null},{"id":"2309.07911","title":"Disentangling Spatial and Temporal Learning for Efficient Image-to-Video Transfer Learning","created":"2023-09-14","cited_by_count":32,"area":null},{"id":"2401.01736","title":"Few-shot Adaptation of Multi-modal Foundation Models: A Survey","created":"2024-01-03","cited_by_count":28,"area":null},{"id":"2501.18592","title":"Advances in Multimodal Adaptation and Generalization: From Traditional Approaches to Foundation Models","created":"2025-01-30","cited_by_count":23,"area":null},{"id":"2308.08414","title":"Tem-adapter: Adapting Image-Text Pretraining for Video Question Answer","created":"2023-08-16","cited_by_count":22,"area":null},{"id":"2410.02924","title":"RSA: Resolving Scale Ambiguities in Monocular Depth Estimators through Language Descriptions","created":"2024-10-03","cited_by_count":21,"area":null},{"id":"2311.09191","title":"Domain Aligned CLIP for Few-shot Classification","created":"2023-11-15","cited_by_count":16,"area":null},{"id":"2402.15726","title":"CLIPose: Category-Level Object Pose Estimation with Pre-trained Vision-Language Knowledge","created":"2024-02-24","cited_by_count":16,"area":null},{"id":"2401.04651","title":"Learning to Prompt Segment Anything Models","created":"2024-01-09","cited_by_count":13,"area":null},{"id":"2407.14020","title":"NeuroBind: Towards Unified Multimodal Representations for Neural Signals","created":"2024-07-19","cited_by_count":13,"area":null},{"id":"2504.12104","title":"Logits DeConfusion with CLIP for Few-Shot Learning","created":"2025-04-16","cited_by_count":11,"area":null},{"id":"2311.01025","title":"Integrating Language-Derived Appearance Elements with Visual Cues in Pedestrian Detection","created":"2023-11-02","cited_by_count":10,"area":null},{"id":"2412.11375","title":"Text and Image Are Mutually Beneficial: Enhancing Training-Free Few-Shot Classification with CLIP","created":"2024-12-16","cited_by_count":6,"area":null},{"id":"2408.08125","title":"Category-Prompt Refined Feature Learning for Long-Tailed Multi-Label Image Classification","created":"2024-08-15","cited_by_count":5,"area":null},{"id":"2306.04715","title":"UniBoost: Unsupervised Unimodal Pre-training for Boosting Zero-shot Vision-Language Tasks","created":"2023-06-07","cited_by_count":4,"area":null},{"id":"2404.19299","title":"Robust Pedestrian Detection via Constructing Versatile Pedestrian Knowledge Bank","created":"2024-04-30","cited_by_count":3,"area":null},{"id":"2509.17747","title":"Dual-View Alignment Learning with Hierarchical-Prompt for Class-Imbalance Multi-Label Classification","created":"2025-09-22","cited_by_count":2,"area":null}],"next_cursor":null}