{"total":21,"rows":[{"id":"2312.14074","title":"LiDAR-LLM: Exploring the Potential of Large Language Models for 3D LiDAR Understanding","created":"2023-12-21","cited_by_count":95,"area":"mllm"},{"id":"2501.01163","title":"3D-LLaVA: Towards Generalist 3D LMMs with Omni Superpoint Transformer","created":"2025-01-02","cited_by_count":68,"area":"mllm"},{"id":"2503.00513","title":"Inst3D-LMM: Instance-Aware 3D Scene Understanding with Multi-modal Instruction Tuning","created":"2025-03-01","cited_by_count":51,"area":"mllm"},{"id":"2502.04263","title":"Cross the Gap: Exposing the Intra-modal Misalignment in CLIP via Modality Inversion","created":"2025-02-06","cited_by_count":43,"area":"mllm"},{"id":"2410.21802","title":"Text-Guided Attention is All You Need for Zero-Shot Robustness in Vision-Language Models","created":"2024-10-29","cited_by_count":23,"area":"mllm"},{"id":"2407.06084","title":"3D Vision and Language Pretraining with Large-Scale Synthetic Data","created":"2024-07-08","cited_by_count":21,"area":"mllm"},{"id":"2403.09296","title":"Select and Distill: Selective Dual-Teacher Knowledge Transfer for Continual Learning on Vision-Language Models","created":"2024-03-14","cited_by_count":19,"area":"mllm"},{"id":"2407.03056","title":"Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge Distillation","created":"2024-07-03","cited_by_count":18,"area":"mllm"},{"id":"2402.04655","title":"Open-Vocabulary Calibration for Fine-tuned CLIP","created":"2024-02-07","cited_by_count":15,"area":"mllm"},{"id":"2410.02681","title":"Understanding and Mitigating Miscalibration in Prompt Tuning for Vision-Language Models","created":"2024-10-03","cited_by_count":9,"area":"mllm"},{"id":"2505.05163","title":"Probabilistic Embeddings for Frozen Vision-Language Models: Uncertainty Quantification with Gaussian Process Latent Variable Models","created":"2025-05-08","cited_by_count":9,"area":"mllm"},{"id":"2601.22828","title":"Decomposing and Composing: Towards Efficient Vision-Language Continual Learning via Rank-1 Expert Pool in a Single LoRA","created":"2026-01-30","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":"2603.27507","title":"Chat-Scene++: Exploiting Context-Rich Object Identification for 3D LLM","created":"2026-03-29","cited_by_count":2,"area":"mllm"},{"id":"2507.20110","title":"NeuroVoxel-LM: Language-Aligned 3D Perception via Dynamic Voxelization and Meta-Embedding","created":"2025-07-27","cited_by_count":1,"area":"mllm"},{"id":"2512.12822","title":"Lemon: A Unified and Scalable 3D Multimodal Model for Universal Spatial Understanding","created":"2025-12-14","cited_by_count":1,"area":"mllm"},{"id":"2510.02913","title":"Improving Adversarial Robustness of Zero-Shot CLIP with Confidence-Aware Weighting","created":"2025-10-03","cited_by_count":0,"area":"mllm"},{"id":"2510.26271","title":"Distilling Multilingual Vision-Language Models: When Smaller Models Stay Multilingual","created":"2025-10-30","cited_by_count":0,"area":"mllm"},{"id":"2511.21191","title":"Scenes as Tokens: Multi-Scale Normal Distributions Transform Tokenizer for General 3D Vision-Language Understanding","created":"2025-11-26","cited_by_count":0,"area":"mllm"},{"id":"2511.22961","title":"HMR3D: Hierarchical Multimodal Representation for 3D Scene Understanding with Large Vision-Language Model","created":"2025-11-28","cited_by_count":0,"area":"mllm"},{"id":"2603.18598","title":"Complementary Text-Guided Attention for Zero-Shot Adversarial Robustness","created":"2026-03-19","cited_by_count":0,"area":"mllm"}],"next_cursor":null}