{"total":23,"rows":[{"id":"2410.13882","title":"Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model","created":"2024-10-03","cited_by_count":96,"area":"mllm"},{"id":"2312.02980","title":"GPT4Point: A Unified Framework for Point-Language Understanding and Generation","created":"2023-12-05","cited_by_count":71,"area":"mllm"},{"id":"2411.16856","title":"SAR3D: Autoregressive 3D Object Generation and Understanding via Multi-scale 3D VQVAE","created":"2024-11-25","cited_by_count":39,"area":"mllm"},{"id":"2506.01853","title":"ShapeLLM-Omni: A Native Multimodal LLM for 3D Generation and Understanding","created":"2025-06-02","cited_by_count":38,"area":"mllm"},{"id":"2503.18476","title":"Global-Local Tree Search in VLMs for 3D Indoor Scene Generation","created":"2025-03-24","cited_by_count":29,"area":"mllm"},{"id":"2512.12768","title":"CoRe3D: Collaborative Reasoning as a Foundation for 3D Intelligence","created":"2025-12-14","cited_by_count":10,"area":"mllm"},{"id":"2405.18937","title":"Kestrel: 3D Multimodal LLM for Part-Aware Grounded Description","created":"2024-05-29","cited_by_count":9,"area":"mllm"},{"id":"2507.00006","title":"MVGBench: Comprehensive Benchmark for Multi-view Generation Models","created":"2025-06-11","cited_by_count":9,"area":"mllm"},{"id":"2503.17827","title":"4D-Bench: Benchmarking Multi-modal Large Language Models for 4D Object Understanding","created":"2025-03-22","cited_by_count":8,"area":"mllm"},{"id":"2602.03890","title":"4DPC$^2$hat: Towards Dynamic Point Cloud Understanding with Failure-Aware Bootstrapping","created":"2026-02-03","cited_by_count":5,"area":"mllm"},{"id":"2606.14699","title":"Instruct-Particulate: Scaling Feed-Forward 3D Object Articulation with Kinematic Control","created":"2026-06-12","cited_by_count":4,"area":"mllm"},{"id":"2503.23062","title":"Shape and Texture Recognition in Large Vision-Language Models","created":"2025-03-29","cited_by_count":3,"area":"mllm"},{"id":"2604.02289","title":"Omni123: Exploring 3D Native Foundation Models with Limited 3D Data by Unifying Text to 2D and 3D Generation","created":"2026-04-02","cited_by_count":3,"area":"mllm"},{"id":"2509.03893","title":"Weakly-Supervised Learning of Dense Functional Correspondences","created":"2025-09-04","cited_by_count":2,"area":"mllm"},{"id":"2603.22782","title":"Know3D: Prompting 3D Generation with Knowledge from Vision-Language Models","created":"2026-03-24","cited_by_count":2,"area":"mllm"},{"id":"2605.10887","title":"Count Anything at Any Granularity","created":"2026-05-11","cited_by_count":1,"area":"mllm"},{"id":"2507.08513","title":"Advancing Multimodal LLMs by Large-Scale 3D Visual Instruction Dataset Generation","created":"2025-07-11","cited_by_count":0,"area":"mllm"},{"id":"2601.04404","title":"3D-Agent:Tri-Modal Multi-Agent Collaboration for Scalable 3D Object Annotation","created":"2026-01-07","cited_by_count":0,"area":"mllm"},{"id":"2602.03533","title":"PnP-U3D: Plug-and-Play 3D Framework Bridging Autoregression and Diffusion for Unified Understanding and Generation","created":"2026-02-03","cited_by_count":0,"area":"mllm"},{"id":"2603.22070","title":"Adapting Point Cloud Analysis via Multimodal Bayesian Distribution Learning","created":"2026-03-23","cited_by_count":0,"area":"mllm"},{"id":"2605.28995","title":"GAP3D: Generative Alignment of VLM Latents to Patch-Level Embeddings for 3D Generation","created":"2026-05-27","cited_by_count":0,"area":"mllm"},{"id":"2608.19726","title":"Projector Is All You Train","created":"2026-08-20","cited_by_count":0,"area":"mllm"},{"id":"2609.05583","title":"An overview of 3D Vision-Language Models","created":"2026-09-04","cited_by_count":0,"area":"mllm"}],"next_cursor":null}