Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation | Paper Citation Record

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This paper cites https://huggingface.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation https://huggingface

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This paper cites GPT-4 Technical Report.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation GPT-4 Technical Report

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Unresolved cited work

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This paper cites Scanqa: 3d question answering for spatial scene understanding.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Scanqa: 3d question answering for spatial scene understanding

Reference 4

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This paper cites Qwen Technical Report.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Qwen Technical Report

Reference 5

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This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 6

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This paper cites Arkitscenes: A diverse real-world dataset for 3d indoor scene understanding using mobile rgb-d data.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Arkitscenes: A diverse real-world dataset for 3d indoor scene understanding using mobile rgb-d data

Reference 7

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This paper cites Audiolm: A language modeling approach to audio generation.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Audiolm: A language modeling approach to audio generation

Reference 8

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This paper cites Large-scale machine learning with stochas- tic gradient descent.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Large-scale machine learning with stochas- tic gradient descent

Reference 9

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This paper cites Language Models are Few-Shot Learners.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Language Models are Few-Shot Learners

Reference 10

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This paper cites Coyo-700m: Image-text pair dataset.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Coyo-700m: Image-text pair dataset

Reference 11

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This paper cites End- to-end object detection with transformers.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation End- to-end object detection with transformers

Reference 12

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This paper cites Emerging properties in self-supervised vision transformers.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Emerging properties in self-supervised vision transformers

Reference 13

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This paper cites Matterport3d: Learning from rgb-d data in indoor environments.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Matterport3d: Learning from rgb-d data in indoor environments

Reference 14

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This paper cites Scanrefer: 3d object localization in rgb-d scans using natural language.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Scanrefer: 3d object localization in rgb-d scans using natural language

Reference 15

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This paper cites Pali: A jointly-scaled multilingual language-image model.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Pali: A jointly-scaled multilingual language-image model

Reference 16

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This paper cites Per-pixel classification is not all you need for semantic segmentation.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Per-pixel classification is not all you need for semantic segmentation

Reference 17

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This paper cites Masked-attention mask transformer for universal image segmentation.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Masked-attention mask transformer for universal image segmentation

Reference 18

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This paper cites Gonzalez, Ion Stoica, and Eric P.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Gonzalez, Ion Stoica, and Eric P

Reference 19

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This paper cites Cat- seg: Cost aggregation for open-vocabulary semantic seg- mentation.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Cat- seg: Cost aggregation for open-vocabulary semantic seg- mentation

Reference 20

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This paper cites 4d spatio-temporal convnets: Minkowski convolutional neural networks.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation 4d spatio-temporal convnets: Minkowski convolutional neural networks

Reference 21

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This paper cites Scaling instruction- finetuned language models.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Scaling instruction- finetuned language models

Reference 22

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This paper cites Pointcept: A codebase for point cloud perception research.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Pointcept: A codebase for point cloud perception research

Reference 23

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Scannet: Richly-annotated 3d reconstructions of indoor scenes

Reference 24

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Procthor: Large-scale embodied ai using procedural generation

Reference 25

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Pengi: An audio language model for audio tasks

Reference 26

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This paper cites Pla: Language-driven open- vocabulary 3d scene understanding.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Pla: Language-driven open- vocabulary 3d scene understanding

Reference 27

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation The Llama 3 Herd of Models

Reference 28

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Efficient graph-based image segmentation

Reference 29

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Dat- acomp: In search of the next generation of multimodal datasets

Reference 30

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Scal- ing open-vocabulary image segmentation with image-level labels

Reference 31

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Imagebind one embedding space to bind them all

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation 3d semantic segmentation with submanifold sparse convolutional networks

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Open- vocabulary object detection via vision and language knowl- edge distillation

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation RegionGPT: Towards Region Understanding Vision Language Model

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Deep residual learning for image recognition

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Denoising diffu- sion probabilistic models

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Scaling up vision-language pre-training for image captioning

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation An Embodied Generalist Agent in 3D World, 2023

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Segment3d: Learning fine-grained class-agnostic 3d segmentation without manual labels

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Open-set image tagging with multi-grained text supervision

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Openins3d: Snap and lookup for 3d open-vocabulary instance segmentation

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Oneformer: One transformer to rule universal image segmentation

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Scen- eVerse: Scaling 3D Vision-Language Learning for Grounded Scene Understanding, 2024

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Scaling up visual and vision-language representa- tion learning with noisy text supervision

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Mistral 7B

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Mixtral of Experts

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Open-vocabulary 3d semantic segmentation with foundation models

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation In defense of lazy visual grounding for open-vocabulary semantic segmentation

Reference 49

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Segment any- thing

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Language-driven semantic seg- mentation

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Semantic-sam: Segment and recognize anything at any gran- ularity

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This paper cites What If We Recaption Billions of Web Images with LLaMA-3?.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation What If We Recaption Billions of Web Images with LLaMA-3?

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Open-vocabulary semantic segmentation with mask-adapted clip

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Improved baselines with visual instruction tuning

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Visual instruction tuning

Reference 58

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This paper cites Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 59

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This paper cites Mmscan: A multi-modal 3d scene dataset with hierarchical grounded language annotations.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Mmscan: A multi-modal 3d scene dataset with hierarchical grounded language annotations

Reference 60

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This paper cites Multiscan: Scalable rgbd scanning for 3d environments with articulated objects.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Multiscan: Scalable rgbd scanning for 3d environments with articulated objects

Reference 61

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This paper cites V-net: Fully convolutional neural networks for volumetric medical image segmentation.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation V-net: Fully convolutional neural networks for volumetric medical image segmentation

Reference 62

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Silc: Improving vision language pretraining with self-distillation

Reference 63

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This paper cites Isbnet: a 3d point cloud instance segmentation network with instance- aware sampling and box-aware dynamic convolution.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Isbnet: a 3d point cloud instance segmentation network with instance- aware sampling and box-aware dynamic convolution

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:52:15.967578Z

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This paper cites Open3dis: Open-vocabulary 3d instance segmentation with 2d mask guidance.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Open3dis: Open-vocabulary 3d instance segmentation with 2d mask guidance

Reference 65

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Improved denoising diffusion probabilistic models

Reference 66

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Unresolved cited work

Reference 67

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Openscene: 3d scene understanding with open vocabularies

Reference 68

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This paper cites Kosmos-2: Grounding Multimodal Large Language Models to the World.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Kosmos-2: Grounding Multimodal Large Language Models to the World

Reference 69

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Language models are un- supervised multitask learners

Reference 70

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This paper cites Learning transferable visual models from natural language supervision.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Learning transferable visual models from natural language supervision

Reference 71

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This paper cites Habitat-matterport 3d dataset (hm3d): 1000 large-scale 3d environments for embodied ai.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Habitat-matterport 3d dataset (hm3d): 1000 large-scale 3d environments for embodied ai

Reference 72

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Denseclip: Language-guided dense prediction with context- aware prompting

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:52:15.852879Z

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Glamm: Pixel grounding large multimodal model

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:52:15.838090Z

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation SAM 2: Segment Anything in Images and Videos

Reference 75

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks

Reference 76

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation High-resolution image synthesis with latent diffusion models

Reference 77

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This paper cites Language- grounded indoor 3d semantic segmentation in the wild.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Language- grounded indoor 3d semantic segmentation in the wild

Reference 78

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This paper cites AudioPaLM: A Large Language Model That Can Speak and Listen.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation AudioPaLM: A Large Language Model That Can Speak and Listen

Reference 79

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This paper cites A multi-view stereo benchmark with high- resolution images and multi-camera videos.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation A multi-view stereo benchmark with high- resolution images and multi-camera videos

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:52:15.796445Z

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This paper cites Laion-5b: An open large-scale dataset for train- ing next generation image-text models.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Laion-5b: An open large-scale dataset for train- ing next generation image-text models

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:52:15.781293Z

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This paper cites Mask3d: Mask trans- former for 3d semantic instance segmentation.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Mask3d: Mask trans- former for 3d semantic instance segmentation

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:52:15.766568Z

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This paper cites Clip-fields: Weakly supervised semantic fields for robotic memory.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Clip-fields: Weakly supervised semantic fields for robotic memory

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:52:15.751438Z

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This paper cites Super-convergence: Very fast training of neural networks using large learning rates.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Super-convergence: Very fast training of neural networks using large learning rates

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:52:15.736995Z

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Denois- ing diffusion implicit models

Reference 85

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Score-based generative modeling through stochastic differential equa- tions

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:52:15.712154Z

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This paper cites Open- mask3d: open-vocabulary 3d instance segmentation.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Open- mask3d: open-vocabulary 3d instance segmentation

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:52:15.697981Z

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This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Gemini: A Family of Highly Capable Multimodal Models

Reference 88

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 89

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation LLaMA: Open and Efficient Foundation Language Models

Reference 90

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This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 91

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Observation 188efec1-78d5-45b2-b1e5-ce0fcf114127 · outbound

This paper cites Rio: 3d object instance re- localization in changing indoor environments.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Rio: 3d object instance re- localization in changing indoor environments

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:52:15.684118Z

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This paper cites Ofa: Unifying architectures, tasks, and modalities through a simple sequence-to-sequence learn- ing framework.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Ofa: Unifying architectures, tasks, and modalities through a simple sequence-to-sequence learn- ing framework

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:52:15.670541Z

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This paper cites EmbodiedScan: A Holistic Multi-Modal 3D Perception Suite Towards Embodied AI, 2023.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation EmbodiedScan: A Holistic Multi-Modal 3D Perception Suite Towards Embodied AI, 2023

Reference 94

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This paper cites Towards Large-scale 3D Representation Learning with Multi-dataset Point Prompt Training.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Towards Large-scale 3D Representation Learning with Multi-dataset Point Prompt Training

Reference 95

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Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Groupvit: Semantic segmentation emerges from text supervision

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:52:15.641360Z

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This paper cites Qwen2 Technical Report.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Qwen2 Technical Report

Reference 97

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This paper cites Regionplc: Regional point-language contrastive learning for open-world 3d scene understanding.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Regionplc: Regional point-language contrastive learning for open-world 3d scene understanding

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:52:15.627270Z

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This paper cites Scannet++: A high-fidelity dataset of 3d in- door scenes.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Scannet++: A high-fidelity dataset of 3d in- door scenes

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:52:15.612383Z

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This paper cites Sai3d: Segment any instance in 3d scenes.

Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation Sai3d: Segment any instance in 3d scenes

Reference 100

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