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Paper Citation Record · LEDGER

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts

As of 8 August 2026, this Paper Citation Record lists 93 of 93 outbound references and 2 inbound Pith citation observations for arXiv:2505.21079.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.21079 v1

Coverage vector

measured 93 of 93 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:46:18.874616Z

measured 95 of 95 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T04:28:28.887051Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-17T22:15:22.050578Z

Reference resolution

93 of 93 outbound references displayed

  • verified exact1
  • verified fuzzy28
  • unresolved64
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation abe1037d-31f3-4496-9bcd-17cc3458f866 · outbound

This paper cites Hierar- chical open-vocabulary 3d scene graphs for language-grounded robot navigation.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Hierar- chical open-vocabulary 3d scene graphs for language-grounded robot navigation

Reference 1

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source=pdf_text observed=2026-08-07T13:46:12.590741Z digest=sha256:54f049c06d3d6c60f0893a3f2de9cbe47f647658721192f66890001d85991bc5

Observation 0e020615-500f-4fae-9edb-73a28b292d0c · outbound

This paper cites Sg-nav: Online 3d scene graph prompting for llm-based zero-shot object navigation.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Sg-nav: Online 3d scene graph prompting for llm-based zero-shot object navigation

Reference 2

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source=pdf_text observed=2026-08-07T13:46:12.656160Z digest=sha256:c5086d6e412c247aaf300efda6722c5511e543373e9f0a261358bc82d00cba67

Observation 66875d4e-66bb-4eda-9f02-e8ec46ad5fd4 · outbound

This paper cites Conceptgraphs: Open-vocabulary 3d scene graphs for perception and planning.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Conceptgraphs: Open-vocabulary 3d scene graphs for perception and planning

Reference 3

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source=pdf_text observed=2026-08-07T13:46:12.709715Z digest=sha256:03a8463c77d244d2aa15e3a89b6c823836dbc92090ca30f8536d4b4b6458459c

Observation 0b088345-0db1-4df2-872f-155d2b587552 · outbound

This paper cites Multi-modal data-efficient 3d scene understanding for autonomous driving.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Multi-modal data-efficient 3d scene understanding for autonomous driving

Reference 4

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source=pdf_text observed=2026-08-07T13:46:12.757264Z digest=sha256:b29495da945040e7fcc7c19c8dc6b90893f01c01397311484f110a17198dc4a7

Observation fae8e8b4-7b35-46bf-9ab1-af8a33b52cd5 · outbound

This paper cites Dme-driver: Integrating human decision logic and 3d scene perception in autonomous driving.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Dme-driver: Integrating human decision logic and 3d scene perception in autonomous driving

Reference 5

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source=pdf_text observed=2026-08-07T13:46:12.826322Z digest=sha256:09d63bfa80e2d2227672282f68fb9a14bed09742cd3cbf54dd1eba0fad216a8c

Observation 0106f186-2589-4936-9d5f-189914c03086 · outbound

This paper cites Drivinggaus- sian: Composite gaussian splatting for surrounding dynamic autonomous driving scenes.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Drivinggaus- sian: Composite gaussian splatting for surrounding dynamic autonomous driving scenes

Reference 6

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source=pdf_text observed=2026-08-07T13:46:12.905153Z digest=sha256:ba5ecbcf075a56ba678977590232175c32cf1129522717c27616513602011af0

Observation d46c641b-4510-45e9-98ae-738e371fd414 · outbound

This paper cites Editable scene simulation for autonomous driving via collaborative llm-agents.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Editable scene simulation for autonomous driving via collaborative llm-agents

Reference 7

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source=pdf_text observed=2026-08-07T13:46:12.979659Z digest=sha256:ff440324ce75604f44cf31dae3f710183e562e332e7333a3d724f594fcd6be83

Observation 93596bd4-263d-4455-8adb-1f4d7365138f · outbound

This paper cites How to enable llm with 3d capacity? a survey of spatial reasoning in llm.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts How to enable llm with 3d capacity? a survey of spatial reasoning in llm

Reference 8

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source=pdf_text observed=2026-08-07T13:46:13.027357Z digest=sha256:719f44136d95054bba95b28cdb0d20ba7af0b97207d146485b9fdbfad07b4abd

Observation 53c7b625-754b-420c-a522-4ec004070c13 · outbound

This paper cites Scenecraft: An llm agent for synthesizing 3d scenes as blender code.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Scenecraft: An llm agent for synthesizing 3d scenes as blender code

Reference 9

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source=pdf_text observed=2026-08-07T13:46:13.059529Z digest=sha256:61d3f4b766c6150e6093baaf48b31c2d50a3ed4378da32c36edb833d5d170fab

Observation 8adc1b71-2718-4873-932d-b18a1222c50c · outbound

This paper cites Scene-LLM: Extending Language Model for 3D Visual Understanding and Reasoning.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Scene-LLM: Extending Language Model for 3D Visual Understanding and Reasoning

Reference 10

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source=pdf_text observed=2026-08-07T13:46:13.113531Z digest=sha256:46069b0648624fbc098cf763b9a8182b5950784051f0edb809f14123dbe87ccd

Observation 55ce2427-d730-489e-881a-b95412075880 · outbound

This paper cites Grounded 3D-LLM with Referent Tokens.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Grounded 3D-LLM with Referent Tokens

Reference 11

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source=pdf_text observed=2026-08-07T13:46:13.184192Z digest=sha256:6ec30a7a241630b0f27addc43b0580014502564f5e86966bcb795a5ed073fa77

Observation 31d7a077-b571-46c9-ae5e-87c0b1ef5c3a · outbound

This paper cites Comp4D: LLM-Guided Compositional 4D Scene Generation.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Comp4D: LLM-Guided Compositional 4D Scene Generation

Reference 12

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source=pdf_text observed=2026-08-07T13:46:13.236790Z digest=sha256:7b478f9753b057886ec1093995865aeefe6bc76c3f0a55124569b24143b5e995

Observation 1f3c1414-9e44-478f-9482-700086ccecaf · outbound

This paper cites Llm-grounder: Open-vocabulary 3d visual grounding with large language model as an agent.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Llm-grounder: Open-vocabulary 3d visual grounding with large language model as an agent

Reference 13

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source=pdf_text observed=2026-08-07T13:46:13.286561Z digest=sha256:436fcaa4694899c2aa0c4eb4ad8d2f9bdcf3079ee288e315018d0139907abb17

Observation 80c3b379-7431-4a6f-a63a-360908578eb8 · outbound

This paper cites Chat-3D: Data-efficiently Tuning Large Language Model for Universal Dialogue of 3D Scenes.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Chat-3D: Data-efficiently Tuning Large Language Model for Universal Dialogue of 3D Scenes

Reference 14

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source=pdf_text observed=2026-08-07T13:46:13.319972Z digest=sha256:b854bac4fc20e2ac3cfaceb1e4cd96ecd621bbde54be07f9479652767a78bc0f

Observation 2f8a92f6-16a5-411d-929d-e212a398ab36 · outbound

This paper cites Chat-scene: Bridging 3d scene and large language models with object identifiers.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Chat-scene: Bridging 3d scene and large language models with object identifiers

Reference 15

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source=pdf_text observed=2026-08-07T13:46:13.372156Z digest=sha256:34314e57199f179bbaa6177a4bab901b9a4f105170f4269bf3c19c4e4a3641c0

Observation 59c48915-716a-45af-a6a2-7de31346977a · outbound

This paper cites GPT4Scene: Understand 3D Scenes from Videos with Vision-Language Models.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts GPT4Scene: Understand 3D Scenes from Videos with Vision-Language Models

Reference 16

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source=pdf_text observed=2026-08-07T13:46:13.435631Z digest=sha256:2c2212913c9b7653be982c9a8e5148a3a436ccdf877252e3f5358c18068272dc

Observation 31acac97-89dd-432e-855f-aef3ea07a7bd · outbound

This paper cites Video-3D LLM: Learning Position-Aware Video Representation for 3D Scene Understanding.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Video-3D LLM: Learning Position-Aware Video Representation for 3D Scene Understanding

Reference 17

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source=pdf_text observed=2026-08-07T13:46:13.494993Z digest=sha256:a9dcd5e0f6b8ceaaa3e109bc1561b78113bdf14bdd4f89917b19720a6f3007f3

Observation c01c3fa4-4a1b-4a66-967e-dce7171274df · outbound

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

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Scanqa: 3d question answering for spatial scene understanding

Reference 18

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source=pdf_text observed=2026-08-07T13:46:13.552321Z digest=sha256:82ee2b4d451c3872f441db57036dd6c96ecb5876728a08b14f0d6569d7a6e29b

Observation 5b4c3c6c-2eaf-420f-8276-b0542cabdb5d · outbound

This paper cites Scan2cap: Context-aware dense captioning in rgb-d scans.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Scan2cap: Context-aware dense captioning in rgb-d scans

Reference 19

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source=pdf_text observed=2026-08-07T13:46:13.583155Z digest=sha256:60961ff3719f6cdbaa7003a2df2b123d4dfb7dce78edfa5ca8fe35d97cd52be4

Observation 0c12676b-a1a9-41a5-b575-7c99e3bc2948 · outbound

This paper cites SQA3D: Situated Question Answering in 3D Scenes.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts SQA3D: Situated Question Answering in 3D Scenes

Reference 20

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source=pdf_text observed=2026-08-07T13:46:13.614106Z digest=sha256:f634f7e42d05a6bbc2219fa57439e83e98dab404f04c684c815d41e61b743dd1

Observation df72ca07-5be0-496b-8169-c3e3f170f8d9 · outbound

This paper cites Pointllm: Empower- ing large language models to understand point clouds.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Pointllm: Empower- ing large language models to understand point clouds

Reference 21

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source=pdf_text observed=2026-08-07T13:46:13.679474Z digest=sha256:cac8a2da1dbd21d45196082ebf658ab9e2d08b1f3d5daa81461f32d6adf8c98e

Observation 1fb51303-b186-4311-81fd-ed0387cc064f · outbound

This paper cites Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction Following.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction Following

Reference 22

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source=pdf_text observed=2026-08-07T13:46:13.736700Z digest=sha256:2c0460ceebccf0fc6b79e4ed7982a0ce80ec69254fb562de94c59632b1640799

Observation fc4dd6aa-075c-4139-82bc-ad69408057e7 · outbound

This paper cites Uni3D-LLM: Unifying Point Cloud Perception, Generation and Editing with Large Language Models.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Uni3D-LLM: Unifying Point Cloud Perception, Generation and Editing with Large Language Models

Reference 23

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source=pdf_text observed=2026-08-07T13:46:13.798999Z digest=sha256:9878a280ea4f956a9cc3db22a6fcd4fc1d6d70c9cbb7062aaef816f05217b35a

Observation 3b8ae0e8-de17-4292-8b25-e5a4f5566296 · outbound

This paper cites Objvariantensemble: Advancing point cloud llm evaluation in chal- lenging scenes with subtly distinguished objects.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Objvariantensemble: Advancing point cloud llm evaluation in chal- lenging scenes with subtly distinguished objects

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:13.876429Z digest=sha256:3ebf303d1d92828d409dba4813725b89c90da233f8e0adddc305cbe3e08f45f2

Observation 56a74583-e0c9-4f22-b7a9-585c3006e47b · outbound

This paper cites Gpt4point: A unified framework for point-language understanding and generation.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Gpt4point: A unified framework for point-language understanding and generation

Reference 25

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source=pdf_text observed=2026-08-07T13:46:13.932284Z digest=sha256:9b205fdc0ce587789d79c3a7e037e350fc1b77b5313e604863b7275ffdb1d299

Observation a6c9804c-9211-426a-9349-80c5d5df308d · outbound

This paper cites Unifying 3d vision-language understanding via promptable queries.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Unifying 3d vision-language understanding via promptable queries

Reference 26

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:14.021149Z digest=sha256:dae2c7879065d9cb7e046718997573b6b824f90d5ae2951cf033cfd144e0ed4b

Observation b2b6703b-7b06-483e-a62b-1b25f607e2a7 · outbound

This paper cites Lidar-llm: Exploring the potential of large language models for 3d lidar understanding.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Lidar-llm: Exploring the potential of large language models for 3d lidar understanding

Reference 27

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raw_fallback, observed 2026-08-07T13:46:23.130721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:14.094545Z digest=sha256:f9677638669360397eb65753ee8842701c6cf102705ab5ff292639a74dcf4522

Observation 2cbf34af-9941-4054-a2e0-7d34e679fe44 · outbound

This paper cites Kestrel: 3D Multimodal LLM for Part-Aware Grounded Description.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Kestrel: 3D Multimodal LLM for Part-Aware Grounded Description

Reference 28

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source=pdf_text observed=2026-08-07T13:46:14.135716Z digest=sha256:e99d5c9769d43712f4f5a92fef53d82e743611522901b605c5af0fee6b35b01a

Observation d49dffac-20ce-4382-8ebd-b66ed401d2c1 · outbound

This paper cites Liba: Language instructed multi-granularity bridge assistant for 3d visual grounding.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Liba: Language instructed multi-granularity bridge assistant for 3d visual grounding

Reference 29

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raw_fallback, observed 2026-08-07T13:46:22.914612Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:14.140769Z digest=sha256:b65c42f9fd2d01c4425aafe260eb751a4ef80976afccb5fb0a2882412cf1ec20

Observation 36cd438f-6601-4aec-b961-09c236eeb544 · outbound

This paper cites 4D-Bench: Benchmarking Multi-modal Large Language Models for 4D Object Understanding.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts 4D-Bench: Benchmarking Multi-modal Large Language Models for 4D Object Understanding

Reference 30

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local_arxiv, observed 2026-08-07T13:46:19.380964Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:14.183457Z digest=sha256:c668b31749158b8c0f170ece598aaeb981f6d15f0fdc039f64521f5f78d8e249

Observation 71c8085a-3bc9-40f3-acc4-0a4af09b6440 · outbound

This paper cites Space3D-Bench: Spatial 3D Question Answering Benchmark.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Space3D-Bench: Spatial 3D Question Answering Benchmark

Reference 31

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source=pdf_text observed=2026-08-07T13:46:14.247666Z digest=sha256:aafeebea1d778b1a050868f59441abf66af14988c7d7a598bc577ea8ba80be10

Observation dfa2a3c7-da90-4b0f-a8a3-343e810bad04 · outbound

This paper cites Embodied Intelligence for 3D Understanding: A Survey on 3D Scene Question Answering.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Embodied Intelligence for 3D Understanding: A Survey on 3D Scene Question Answering

Reference 32

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source=pdf_text observed=2026-08-07T13:46:14.341180Z digest=sha256:1a26a60d86fd9bdca5d225f1dd0535ca1708bd71c2c0330eea8811b0fd6edf35

Observation b26fd254-490e-46e6-b794-35981a26791a · outbound

This paper cites LLaVA-3D: A Simple yet Effective Pathway to Empowering LMMs with 3D-awareness.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts LLaVA-3D: A Simple yet Effective Pathway to Empowering LMMs with 3D-awareness

Reference 33

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source=pdf_text observed=2026-08-07T13:46:14.423259Z digest=sha256:00496d09b574b5d07f68e1b320acca94be5f76684319fa04b4cb95b339a2b010

Observation 58d23528-1edd-4483-a4f0-a17c2c013d05 · outbound

This paper cites 3UR-LLM: An End-to-End Multimodal Large Language Model for 3D Scene Understanding.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts 3UR-LLM: An End-to-End Multimodal Large Language Model for 3D Scene Understanding

Reference 34

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source=pdf_text observed=2026-08-07T13:46:14.473013Z digest=sha256:2beda3552b07399f571ba4a2c01ff1c013e713ce1eecae30840588070b873249

Observation 5a9cbfaa-84a7-43f0-a20b-aa0e4d0e0786 · outbound

This paper cites Sceneverse: Scaling 3d vision-language learning for grounded scene understanding.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Sceneverse: Scaling 3d vision-language learning for grounded scene understanding

Reference 35

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source=pdf_text observed=2026-08-07T13:46:14.529598Z digest=sha256:a1ce5a14b7618eb00682e898ff1c408262e9cf0bed3d14fa09e177da0a25db82

Observation c2fc252e-45b6-4916-941b-f3cca1a8531c · outbound

This paper cites Image as a foreign language: Beit pretraining for vision and vision-language tasks.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Image as a foreign language: Beit pretraining for vision and vision-language tasks

Reference 36

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:14.596999Z digest=sha256:4f835502bbfea539f6875522d9cec15f2d9a9ccc6f8530e7fc5e2c01da291f80

Observation 0abf9120-0f6b-4356-8a78-4edca9689486 · outbound

This paper cites Uni3dl: A unified model for 3d vision- language understanding.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Uni3dl: A unified model for 3d vision- language understanding

Reference 37

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:14.681514Z digest=sha256:30778d405e3beffe8302ceb13cb3aa96efea0969a82cedebe541d17b93ad7f71

Observation c5ee0eaf-dda9-43a5-bfbd-d1e485fde89b · outbound

This paper cites Vision-language pre-training with object contrastive learning for 3d scene understanding.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Vision-language pre-training with object contrastive learning for 3d scene understanding

Reference 38

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:14.742528Z digest=sha256:78dfc51b6723c80ac477380066d0e193afa736cd012058e4c89cf2c1d8c58a21

Observation cf7acec0-b0f4-4617-8774-0a8ffe20e460 · outbound

This paper cites When llms step into the 3d world: A survey and meta-analysis of 3d tasks via multi-modal large language models.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts When llms step into the 3d world: A survey and meta-analysis of 3d tasks via multi-modal large language models

Reference 39

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source=pdf_text observed=2026-08-07T13:46:14.795239Z digest=sha256:d64e51a6c17c2e6f964d29e65911cb27c89af559ea9285b6799826614b422344

Observation 974b4501-a380-4b02-837b-c29974481829 · outbound

This paper cites Mixture-of-experts with expert choice routing.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Mixture-of-experts with expert choice routing

Reference 40

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raw_fallback, observed 2026-08-07T13:46:22.293795Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:14.893770Z digest=sha256:94279f623f5978ff488d6adef3bb4ac70e71c22de3c3bb26b2a52d301ed8b692

Observation f4c6c5b7-6629-4ee2-a0fa-36051bc411c8 · outbound

This paper cites A Survey on Mixture of Experts in Large Language Models.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts A Survey on Mixture of Experts in Large Language Models

Reference 41

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source=pdf_text observed=2026-08-07T13:46:14.957598Z digest=sha256:c4f053d10e0d861490cd0139fe1ff98419358be050f4fbeb5833ca29314bae94

Observation 4e6411fb-704c-43ea-b942-30c9f3e33ffb · outbound

This paper cites Revisiting MoE and Dense Speed-Accuracy Comparisons for LLM Training.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Revisiting MoE and Dense Speed-Accuracy Comparisons for LLM Training

Reference 42

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source=pdf_text observed=2026-08-07T13:46:15.035924Z digest=sha256:a80c454f371f0c1ec078f1f64ef1b2552944618b470b4e5b5e1f0fe3d63d90d1

Observation a6dc91f9-957d-438f-8e46-7b78ec8f0fbc · outbound

This paper cites ProMoE: Fast MoE-based LLM Serving using Proactive Caching.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts ProMoE: Fast MoE-based LLM Serving using Proactive Caching

Reference 43

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source=pdf_text observed=2026-08-07T13:46:15.078213Z digest=sha256:7a434011c797d083781e3160b638b286bb7acd03506e4089449941bc33c325f6

Observation f67659c6-7273-469e-8866-95eb01f56ba6 · outbound

This paper cites OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models

Reference 44

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source=pdf_text observed=2026-08-07T13:46:15.171955Z digest=sha256:821e3d9a9cee6e5fbc77bc6e5898e70d653a9bc8b18dba4b1753c8a11633f506

Observation a6b45c4f-df13-47d0-8e59-5727b1ed5834 · outbound

This paper cites Vlmo: Unified vision-language pre-training with mixture-of-modality-experts.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Vlmo: Unified vision-language pre-training with mixture-of-modality-experts

Reference 45

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verified fuzzy
raw_fallback, observed 2026-08-07T13:46:22.152608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:15.264291Z digest=sha256:8e6cc3cddea799af8b2a73bff943712bf7f4a34cbfe5b9dc0e7e8b1222b990f2

Observation b25f7791-3c29-4b06-a152-e42c32f6c2c6 · outbound

This paper cites Scaling Vision-Language Models with Sparse Mixture of Experts.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Scaling Vision-Language Models with Sparse Mixture of Experts

Reference 46

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source=pdf_text observed=2026-08-07T13:46:15.339882Z digest=sha256:2b9ddb15d1410de34e766d149415fbf0879d461527bb855b2f6ef00c659daff6

Observation 44d5141c-8100-4e17-9fbf-3a6a0fe632e8 · outbound

This paper cites MoE-LLaVA: Mixture of Experts for Large Vision-Language Models.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts MoE-LLaVA: Mixture of Experts for Large Vision-Language Models

Reference 47

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source=pdf_text observed=2026-08-07T13:46:15.416411Z digest=sha256:f89a7ceb2001ab2ee180bab37c1c420a317909abfec7da6ea54f4e7ed34c362c

Observation a776cff8-8824-4d97-b82b-6dd8664a8bb9 · outbound

This paper cites Ada-k routing: Boosting the efficiency of moe-based llms.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Ada-k routing: Boosting the efficiency of moe-based llms

Reference 48

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:15.507691Z digest=sha256:ed5bc368e41dff7b046352566f715ed9147e83f80e5fa111f7fa986f0fa98eb7

Observation 7f745a5f-f77a-49d4-a003-4884aa126729 · outbound

This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity

Reference 49

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source=pdf_text observed=2026-08-07T13:46:15.586583Z digest=sha256:9367ecdff2a7c0388f2dcae369bb078728c30327f87c1a6e48846554eeaeeb0d

Observation dd29c3b7-32ed-4da1-be2b-23990d2161ea · outbound

This paper cites Llama-moe: Building mixture-of-experts from llama with continual pre-training.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Llama-moe: Building mixture-of-experts from llama with continual pre-training

Reference 50

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source=pdf_text observed=2026-08-07T13:46:15.641775Z digest=sha256:d835ccb1d26a87fa83871678b9704a73a471369faf102de985ad9fd2549f5dae

Observation ab168ca7-d01a-44f8-9e8c-3d866fc399aa · outbound

This paper cites Uni-moe: Scaling unified multimodal llms with mixture of experts.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Uni-moe: Scaling unified multimodal llms with mixture of experts

Reference 51

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raw_fallback, observed 2026-08-07T13:46:21.874331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:15.679963Z digest=sha256:48c5643c399883ab4d7efc94e6232c8c479bf91e30ba5660fdb0900f801c41ea

Observation ec264051-b15b-4672-ad89-4c4289841fd2 · outbound

This paper cites 3D-MoE: A Mixture-of-Experts Multi-modal LLM for 3D Vision and Pose Diffusion via Rectified Flow.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts 3D-MoE: A Mixture-of-Experts Multi-modal LLM for 3D Vision and Pose Diffusion via Rectified Flow

Reference 52

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source=pdf_text observed=2026-08-07T13:46:15.744253Z digest=sha256:6dfdb347cd594889df1758487a7f5d78ae15f54edbfbae522426c3fbb3779f0a

Observation b39e2d56-872c-4d1e-953c-087506ebb4cf · outbound

This paper cites Minigpt-3d: Efficiently aligning 3d point clouds with large language models using 2d priors.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Minigpt-3d: Efficiently aligning 3d point clouds with large language models using 2d priors

Reference 53

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raw_fallback, observed 2026-08-07T13:46:21.795066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:15.796253Z digest=sha256:6eed73309e02c17713bfa138211a41815fe4b261208cbee8cbf960b388ed05ef

Observation 9d0e7d08-ea5f-4681-8d38-ac38b5b22f3c · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts DINOv2: Learning Robust Visual Features without Supervision

Reference 54

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source=pdf_text observed=2026-08-07T13:46:15.889974Z digest=sha256:c58483f6fac971f6af5eaf396478d721d9c6399760768c05bf6933e5910a57bc

Observation 9900a261-95af-4cf3-96b6-77ae5aa9c000 · outbound

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

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Learning transferable visual models from natural language supervision

Reference 55

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raw_fallback, observed 2026-08-07T13:46:21.704411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:15.929697Z digest=sha256:66c95259b91ba236f75a39f7bf7974d321ccb94f622dfedb515693101f95dfa4

Observation a50b727f-c45f-49bd-a102-77120c739898 · outbound

This paper cites Pointnet++: Deep hierarchical feature learning on point sets in a metric space.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Pointnet++: Deep hierarchical feature learning on point sets in a metric space

Reference 56

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source=pdf_text observed=2026-08-07T13:46:15.963506Z digest=sha256:7a2012bafdaaee6c5d9aba0b00e0268acbf26fda8d42fcba18237fefd6661de7

Observation 8dd7b16f-a899-4752-a93f-7586404e5a80 · outbound

This paper cites Mask3d: Mask transformer for 3d semantic instance segmentation.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Mask3d: Mask transformer for 3d semantic instance segmentation

Reference 57

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source=pdf_text observed=2026-08-07T13:46:16.039764Z digest=sha256:2dcd0db294818b3a297ac87488dc5f29c7862b7051e523c2c2b47408790d2102

Observation d4fc414e-856d-4cc6-be66-fcf3f8a21dc4 · outbound

This paper cites Scannet: Richly-annotated 3d reconstructions of indoor scenes.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Scannet: Richly-annotated 3d reconstructions of indoor scenes

Reference 58

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source=pdf_text observed=2026-08-07T13:46:16.132585Z digest=sha256:a21749a5bd1f57fca2eb0476a40e502ab7d5031277bef6e416eecf97c31fd999

Observation e62bd513-2842-4d28-9f94-4c3d807f284d · outbound

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

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Scanrefer: 3d object localization in rgb-d scans using natural language

Reference 59

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source=pdf_text observed=2026-08-07T13:46:16.200732Z digest=sha256:c306156c786917b38cdc3a3b04f5877ddd69c5c63be8995daa223716babe1684

Observation f138a48c-270f-4626-abab-eb9a6e134db9 · outbound

This paper cites Multi3drefer: Grounding text description to multiple 3d objects.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Multi3drefer: Grounding text description to multiple 3d objects

Reference 60

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raw_fallback, observed 2026-08-07T13:46:21.544501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:16.245785Z digest=sha256:5dea9266308ce3e85fd7cff0c1d9e30d9a2c436e4a1250e8e1f25d2d34577f2c

Observation 41cd88d9-8585-4d71-b565-5a69a56e54f6 · outbound

This paper cites Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023

Reference 61

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source=pdf_text observed=2026-08-07T13:46:16.300556Z digest=sha256:4784e9ca2adda66b2a6328087c4d9415c517dfddba5ad46e184d2cd6e3cc5ae7

Observation 8504db6e-dd20-4c52-a550-76c5b5c5afae · outbound

This paper cites Ross3D: Reconstructive Visual Instruction Tuning with 3D-Awareness.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Ross3D: Reconstructive Visual Instruction Tuning with 3D-Awareness

Reference 62

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source=pdf_text observed=2026-08-07T13:46:16.379978Z digest=sha256:38fb8368523be69efe5e61d427795f1d986a416da0288ab0b670e19941215bb9

Observation 40031675-6144-4b68-a221-1d878f6e210a · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Bleu: a method for automatic evaluation of machine translation

Reference 63

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source=pdf_text observed=2026-08-07T13:46:16.425498Z digest=sha256:fe359aa212bb1a1a93e64a960b147a8251f4af20f61592f8a2fb8bac4cfd6a86

Observation ee138cc5-f44e-4883-ba44-1dbf94c066b0 · outbound

This paper cites Meteor: An automatic metric for mt evaluation with improved correlation with human judgments.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Meteor: An automatic metric for mt evaluation with improved correlation with human judgments

Reference 64

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source=pdf_text observed=2026-08-07T13:46:16.457621Z digest=sha256:7a323a46f5e477a031ddddb8208f30e8abe344fb460bccc827274f7b0ce45ed5

Observation 38de929c-ac86-41a9-9fc0-e410279ffcab · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Rouge: A package for automatic evaluation of summaries

Reference 65

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source=pdf_text observed=2026-08-07T13:46:16.494360Z digest=sha256:f8a4c7853c49ecea0644ba44d78303e9b884b52ef0752c060df37ea1af6a3980

Observation 7d724260-e5ea-4175-8c9d-ca14fe7e6c5a · outbound

This paper cites Cider: Consensus-based image description evaluation.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Cider: Consensus-based image description evaluation

Reference 66

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source=pdf_text observed=2026-08-07T13:46:16.515497Z digest=sha256:4d4ffd478790905ca6750795e6a71a770a544a5db148c0719f27a473917d5c8c

Observation fab14a4f-c41b-4382-9de3-42f4c6b02548 · outbound

This paper cites Context-aware alignment and mutual masking for 3d-language pre-training.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Context-aware alignment and mutual masking for 3d-language pre-training

Reference 67

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verified fuzzy
raw_fallback, observed 2026-08-07T13:46:21.433344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:16.563766Z digest=sha256:51f84713ac13f436991ed616555574756eff81c9646bd6571a68b3462483e4c6

Observation a461d938-a693-48f4-b239-95aa8b05a8b0 · outbound

This paper cites 3d-vista: Pre-trained transformer for 3d vision and text alignment.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts 3d-vista: Pre-trained transformer for 3d vision and text alignment

Reference 68

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source=pdf_text observed=2026-08-07T13:46:16.625470Z digest=sha256:463bfeb41212f8e0a433bfec5fdb32c5e1ec1e05c9a2719c54b878ccabcbf34a

Observation a11f7e75-7d53-4f32-8fc8-0fb0710c46c6 · outbound

This paper cites InternVL-X: Advancing and Accelerating InternVL Series with Efficient Visual Token Compression.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts InternVL-X: Advancing and Accelerating InternVL Series with Efficient Visual Token Compression

Reference 69

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source=pdf_text observed=2026-08-07T13:46:16.681525Z digest=sha256:879d4a6a0c4b6ad05b39baec45c9b97e0678630497c0f5e841fc29aebcbd1a4e

Observation 2d9e9fbe-b150-4716-a71a-1cf7ec52cda5 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 70

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:46:16.756757Z digest=sha256:f5190f1ce443fbe4fcaf03eacb83694c65e5a262e31801faf6f43cc719a0a116

Observation 123279b9-48f2-448e-98d8-9f2e0c7aed8f · outbound

This paper cites LLaVA-Video: Video Instruction Tuning With Synthetic Data.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts LLaVA-Video: Video Instruction Tuning With Synthetic Data

Reference 71

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no resolver link, observed 2026-08-07T13:46:16.849356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:46:16.849356Z digest=sha256:49511e4298c6e4a651679be67b73c58a292f660d2acda8b15fc7114e0423eadb

Observation 12c600fc-3b43-4561-a1ad-6e931994fde7 · outbound

This paper cites Lamm: Language-assisted multi-modal instruction-tuning dataset, framework, and benchmark.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Lamm: Language-assisted multi-modal instruction-tuning dataset, framework, and benchmark

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:46:21.316454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:16.948131Z digest=sha256:9e7beb05191441fea6f0f76bc114e6a5edf327196172c7d0f4528bc35dde6aa6

Observation fde67467-ac28-41b9-8fff-4ab2b418bd52 · outbound

This paper cites 3d-llm: Injecting the 3d world into large language models.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts 3d-llm: Injecting the 3d world into large language models

Reference 73

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no resolver link, observed 2026-08-07T13:46:17.076369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:46:17.076369Z digest=sha256:cf9f797419f2e6c19a80d4a5f345547483e49ffe5d08bd85da2e4c963ac1e424

Observation f1d2de7e-81d4-459f-9cda-97874fd4f2d5 · outbound

This paper cites Chat-Scene: Bridging 3D Scene and Large Language Models with Object Identifiers.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Chat-Scene: Bridging 3D Scene and Large Language Models with Object Identifiers

Reference 74

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:46:17.141359Z digest=sha256:575e91ad66dae9304b88ef2a659e3f866c1496e71a23261500dfb215d8425040

Observation b896d076-9b48-4ca8-b16b-c194431e4349 · outbound

This paper cites Ll3da: Visual interactive instruction tuning for omni-3d understanding reasoning and planning.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Ll3da: Visual interactive instruction tuning for omni-3d understanding reasoning and planning

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:46:21.190400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:17.215388Z digest=sha256:c37bcd0251b4de0a3b8dfd2677290870901ddac52094b8fa3961aa41be63afdb

Observation 59aa549d-4755-4f82-9b60-f94b16bdc241 · outbound

This paper cites An Embodied Generalist Agent in 3D World.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts An Embodied Generalist Agent in 3D World

Reference 76

Resolution
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no resolver link, observed 2026-08-07T13:46:17.324846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:46:17.324846Z digest=sha256:71cefcc666562b24acd70c119d9b47487e066c966325e74a47fe4ca00950c2df

Observation 20c4dede-de2a-4823-9071-1ec931fa9b06 · outbound

This paper cites Principal components analysis (pca).

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Principal components analysis (pca)

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:46:21.080412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:17.434535Z digest=sha256:d1f759a4c830d4db4ad78609127abf9f51d7cbcd8e1dafd6ffe011bd3b5b8e50

Observation 5b455741-a976-4bd0-921d-51a0d97dbf53 · outbound

This paper cites 3djcg: A unified framework for joint dense captioning and visual grounding on 3d point clouds.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts 3djcg: A unified framework for joint dense captioning and visual grounding on 3d point clouds

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:46:20.967618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:17.554741Z digest=sha256:2a31ceb977b24e3bab8c849969dfdbc7864cb8e7a55466e33ef448717afc29d3

Observation 4f9e6749-68c8-4694-aa86-00fe14be757c · outbound

This paper cites End-to-end 3d dense captioning with vote2cap-detr.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts End-to-end 3d dense captioning with vote2cap-detr

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:46:20.892441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:17.671882Z digest=sha256:e90f9207f7969f8746690d7ad090291b836840348bcd20358c8f8c483729a773

Observation 407a0d21-38d9-435a-b446-64c737fc95eb · outbound

This paper cites X-trans2cap: Cross-modal knowledge transfer using transformer for 3d dense captioning.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts X-trans2cap: Cross-modal knowledge transfer using transformer for 3d dense captioning

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:46:20.765740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:17.746676Z digest=sha256:301bea401cd96d7559fb890ae1e809229e99c8becdc0d0ad2ac29cda0866c403

Observation 8cdb7196-3760-4303-a22a-0f95b1a3480d · outbound

This paper cites MVT: Multi-view Vision Transformer for 3D Object Recognition.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts MVT: Multi-view Vision Transformer for 3D Object Recognition

Reference 81

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:46:17.813022Z digest=sha256:d4c906c2a4c93d7e11c4aface024be940fe4ab25105f1a72e470964dfbd9c8a7

Observation 7438619f-e002-4e53-97e7-4dff0e2a6e5b · outbound

This paper cites 3dvg-transformer: Relation modeling for visual grounding on point clouds.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts 3dvg-transformer: Relation modeling for visual grounding on point clouds

Reference 82

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source=pdf_text observed=2026-08-07T13:46:17.891316Z digest=sha256:9c9420128e3007751d2828c00cc4ff3950adc57f873cf21b76b1ca12f6c107cc

Observation c3f666bd-9bc5-431a-83a9-3e99b6aa9ec4 · outbound

This paper cites Language conditioned spatial relation reasoning for 3d object grounding.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Language conditioned spatial relation reasoning for 3d object grounding

Reference 83

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no resolver link, observed 2026-08-07T13:46:17.973560Z

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source=pdf_text observed=2026-08-07T13:46:17.973560Z digest=sha256:468ab1a0e028281c055791bb6445b78663e675eef9ae5270b7ebe0e96dfe0e45

Observation b1a8eeff-6005-43f8-a02d-35249b7e51d2 · outbound

This paper cites Less is more: Clipbert for video-and-language learning via sparse sampling.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Less is more: Clipbert for video-and-language learning via sparse sampling

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:46:20.643575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:18.077406Z digest=sha256:d8dde53d131f68438ba80210c0e1bb5a3052c42c3c3c255919a90a1f56320035

Observation d502179a-f70d-436b-beb5-3d0aed48b469 · outbound

This paper cites Text-guided graph neural networks for referring 3d instance segmentation.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Text-guided graph neural networks for referring 3d instance segmentation

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:46:20.435493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:18.161114Z digest=sha256:d8ad06464a1efed3f8f671965a88b08b9940a301b8959bbc106c9b67a5c860bd

Observation fb3fdcde-5000-4ef4-b0d5-4f987f3f9322 · outbound

This paper cites In- stancerefer: Cooperative holistic understanding for visual grounding on point clouds through instance multi-level contextual referring.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts In- stancerefer: Cooperative holistic understanding for visual grounding on point clouds through instance multi-level contextual referring

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:46:20.326600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:18.270692Z digest=sha256:719fc06a70ab057214e4632a753196656b331d435a407b27f09deff2d67dd038

Observation 19ee3c74-9ecb-4d4d-a1cb-2f1b8e355a85 · outbound

This paper cites 3d-sps: Single-stage 3d visual grounding via referred point progressive selection.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts 3d-sps: Single-stage 3d visual grounding via referred point progressive selection

Reference 87

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no resolver link, observed 2026-08-07T13:46:18.389743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:46:18.389743Z digest=sha256:659cdd52a84dfffa225d15424c3429fd6d0472542dbab0a90fa81be92c39b1c4

Observation 9595cc4c-1e4c-4f43-b63d-3fcfb8f4460a · outbound

This paper cites D3net: A speaker-listener architecture for semi-supervised dense captioning and visual grounding in rgb-d scans.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts D3net: A speaker-listener architecture for semi-supervised dense captioning and visual grounding in rgb-d scans

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:46:20.194643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:18.491669Z digest=sha256:f3934afb92f4a3393e3958525a933731ff5e81a99d1f3e423ce9fda29f66d731

Observation e307ec8a-2d47-4424-a4bc-f77ca43fa1c3 · outbound

This paper cites Bottom up top down detection transformers for language grounding in images and point clouds.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Bottom up top down detection transformers for language grounding in images and point clouds

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:46:20.036900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:18.602704Z digest=sha256:eb55b244edb7b4767bb4a20e79c98d3c4737a70f99a253fd3f8db0a1609fc92d

Observation 7a183bd7-3cec-47e5-9641-643389b45c1f · outbound

This paper cites Learning Point-Language Hierarchical Alignment for 3D Visual Grounding.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Learning Point-Language Hierarchical Alignment for 3D Visual Grounding

Reference 90

Resolution
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no resolver link, observed 2026-08-07T13:46:18.684551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:46:18.684551Z digest=sha256:805e8d308d4a7b6e4e8f46f9d92458de961fafd8161b132e0b80d660f014e3dc

Observation 75982f4f-e0f7-44c8-aaef-8312fa98d3bc · outbound

This paper cites 3DRP-Net: 3D Relative Position-aware Network for 3D Visual Grounding.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts 3DRP-Net: 3D Relative Position-aware Network for 3D Visual Grounding

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-07T13:46:18.790770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:46:18.790770Z digest=sha256:ed00ec8b3456e19d87940979c4d85e38c8d246d56637cfed5e058f8a6b9bb8a3

Observation 8fa273ce-e506-408c-8999-0442de193403 · outbound

This paper cites Eda: Explicit text-decoupling and dense alignment for 3d visual grounding.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts Eda: Explicit text-decoupling and dense alignment for 3d visual grounding

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:46:19.857840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:18.827522Z digest=sha256:0c716d6d362575919e537b371488c5412c506da9a1e92c98c0ebe7032c9c852a

Observation bdfbdf3c-1840-450a-abc8-6f0425535a05 · outbound

This paper cites the bed, which is rectangular in shape, is located adjacent to the door.

Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts the bed, which is rectangular in shape, is located adjacent to the door

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:46:19.736225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:46:18.874616Z digest=sha256:5c1c16067c6e6f882ad07dc654ca15bf5f1452e0d2bd1106ae91aeb909abe9e9

Pith citing papers

Observation 5b933114-d814-4c29-94b1-37285e3b4ebb · inbound

DoReMi: Bridging 3D Domains via Topology-Aware Domain-Representation Mixture of Experts cites this paper.

DoReMi: Bridging 3D Domains via Topology-Aware Domain-Representation Mixture of Experts Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:15:22.052701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-17T22:12:51.364157Z digest=sha256:5bc1934bd42814ef49661443f8daf59fc4e0d46e32c717535b52cc2fdade2085

Observation 15f2ecf4-f69a-407a-b325-57b9f5e01fa5 · inbound

SmartMage: Dynamic Modality Orchestration for 3D Scene Understanding cites this paper.

SmartMage: Dynamic Modality Orchestration for 3D Scene Understanding Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Experts

Reference 88

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unresolved
no resolver link, observed 2026-08-06T04:28:28.887051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:28:28.887051Z digest=sha256:abb8bd6a6ee4a55e159c07fdf56c8bf1cd9546abedd1b5e9bf55577131bab4a4