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Paper Citation Record · LEDGER

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding

As of 18 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 4 inbound Pith citation observations for arXiv:2412.18450.

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

pith.paper-citation-record.v1
2412.18450 v3

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T04:45:36.878751Z

measured 74 of 74 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:03:03.534576Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-08T02:44:27.709058Z

Reference resolution

70 of 70 outbound references displayed

  • verified exact0
  • verified fuzzy51
  • unresolved19
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c14a5eb6-2e6e-423c-b53f-6a4424b974b4 · outbound

This paper cites Referit3d: Neural listeners for fine-grained 3d object identification in real-world scenes.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Referit3d: Neural listeners for fine-grained 3d object identification in real-world scenes

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.843273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.577857Z digest=sha256:1d8da79ba0e736d14d5fcef94d5a6d03cd6dd7bd285886d64464ff3483ee3956

Observation 92accb02-a146-47fc-b5f6-93451e558c9b · outbound

This paper cites Llama 3 model card.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Llama 3 model card

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.829855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.582994Z digest=sha256:e51279686b0eb8344f847bc48a3c48a084d00bacc556f6958f1dd90d8ce0da8e

Observation 4ef2d1c2-ceb2-45d4-abd0-24ab5ed737c1 · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Scanqa: 3d question answering for spatial scene understanding

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.816352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.587914Z digest=sha256:fa5be033ca5c2383ce518d80ed6fba659b3be8f44843f89ff70df53728e8aaef

Observation 4536cdb4-728c-4ade-a01f-ca6637ae1a73 · outbound

This paper cites Context-Aware Entity Grounding with Open-Vocabulary 3D Scene Graphs.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Context-Aware Entity Grounding with Open-Vocabulary 3D Scene Graphs

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.592429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.592429Z digest=sha256:16117cd5d0a6192d77cdf9a7a234af08cc730a38d01ad93b22b6e00bae37d307

Observation e623daae-4cee-4c53-af84-9f1014d6bff9 · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Scanrefer: 3d object localization in rgb-d scans using natural language

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.803874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.597235Z digest=sha256:53043bd617bb51569ab82c1528ceb49945c56d9afbc85620607a9b8b52fa4081

Observation ee817833-0af0-402b-88fc-ea50081a12eb · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Language conditioned spatial relation reasoning for 3d object grounding

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.601647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.601647Z digest=sha256:01ca959a38285127b836cde1650ad24862d9e0d0d10e5c744601938c93f11c90

Observation dee1d8d7-06a0-4d5d-8794-763c0a600069 · outbound

This paper cites Ll3da: Visual interactive instruction tuning for omni-3d understand- ing, reasoning, and planning, 2023.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Ll3da: Visual interactive instruction tuning for omni-3d understand- ing, reasoning, and planning, 2023

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.782267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.606140Z digest=sha256:30bc414a0abedff9665a83b9e7f980badd6b3e0f7d6c8412afb844a9cbda23ae

Observation 1fc2a2b5-351d-4e0c-ab64-70138ae7537b · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Grounded 3D-LLM with Referent Tokens

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.610992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.610992Z digest=sha256:ed6d12def5c07fe33e98e578584260ec959f7bd5b13715d6710bd119baccd0c1

Observation 52fbef19-02fa-4dc4-b773-29ff12916935 · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Scan2cap: Context-aware dense captioning in rgb- d scans

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.768952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.615751Z digest=sha256:c016ffaf6ceac56455b4d354d3378d97beba45c843adbd67d73e70953f64326a

Observation 130f8898-d5e3-45b6-ab5c-43f72c5e6c5d · outbound

This paper cites SpatialRGPT: Grounded Spatial Reasoning in Vision Language Models.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding SpatialRGPT: Grounded Spatial Reasoning in Vision Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.620135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.620135Z digest=sha256:070436bc717708228cc52984b56d15f259c1e544f4b4594dbd1e189883d30982

Observation c2ffb367-7fb2-440f-a513-480ac499bf1d · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Scannet: Richly-annotated 3d reconstructions of indoor scenes

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.754821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.624729Z digest=sha256:c832c0292c3a9a0a0a7abb044b9bb9f92fe9f5f0c94f114046d16936560e6c76

Observation 31f07439-f6bb-463c-9afc-7355d1654b23 · outbound

This paper cites Multi-CLIP: Contrastive Vision-Language Pre-training for Question Answering tasks in 3D Scenes.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Multi-CLIP: Contrastive Vision-Language Pre-training for Question Answering tasks in 3D Scenes

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.628677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.628677Z digest=sha256:5ef7997780e55c2633fd3ed81831ee511ef8aa7eaa5e54301ce7e65925ae1892

Observation cd736c78-a91e-425b-975f-a3f6dba0b57b · outbound

This paper cites Scenegenie: Scene graph guided diffusion models for image synthesis.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Scenegenie: Scene graph guided diffusion models for image synthesis

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.741294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.633034Z digest=sha256:fb4caf540c36188a325c887a9b6e0990e3a7027b4a99289451838efb5021bc6e

Observation 0e0b409f-76a3-40f0-ba2e-2720cb107490 · outbound

This paper cites Free-form description guided 3d visual graph network for object grounding in point cloud.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Free-form description guided 3d visual graph network for object grounding in point cloud

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.727323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.637244Z digest=sha256:dff684bbca1fa7fc4c8729ae4f533b683c4b7eebd89c579ca58005cdc123baf2

Observation e872f5b6-d329-44dc-ae47-8d18063d0b4b · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Scene-LLM: Extending Language Model for 3D Visual Understanding and Reasoning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.641435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.641435Z digest=sha256:5b9c3b2ebc88d39f030783f5566a5aed96e4eb73628d0d34403fdbe9327564c2

Observation 6d375d1d-1849-4e2d-bfba-e580f8c1f25b · outbound

This paper cites Graphdreamer: Compositional 3d scene synthesis from scene graphs.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Graphdreamer: Compositional 3d scene synthesis from scene graphs

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.713483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.645986Z digest=sha256:0419fc43839c074a05df3be07654f12cf36275ff16bb2b634159c4ae92f21f9c

Observation b9ed464a-dfc1-423c-bf2a-e3dc9e8ed2d1 · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Concept- graphs: Open-vocabulary 3d scene graphs for perception and planning

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.699563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.650175Z digest=sha256:7197102ffc49ee9c9bb7eabcf9ec3e1c42c0bac940fae5b022aee4fe947460bd

Observation 27a13b60-6c6f-4c4f-9870-29305ff5049f · outbound

This paper cites Zero-shot referring expression comprehension via structural similarity between images and captions.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Zero-shot referring expression comprehension via structural similarity between images and captions

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.686646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.654127Z digest=sha256:43490a5486b3d33a0de535fe35eade82eb6e52512f0604467adb2433e2dd05a0

Observation cc95ae88-526f-4c96-b434-d3b00e95b536 · outbound

This paper cites Relation-wise transformer network and reinforcement learning for visual navigation.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Relation-wise transformer network and reinforcement learning for visual navigation

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.673483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.658428Z digest=sha256:1d9ddd8f6a65cf9c953d9db8e77b13e39d0e4533576095e3a8c7d575299a2863

Observation d30d82ac-0ae9-41f6-b2fd-4152fd3a691b · outbound

This paper cites Language-grounded dy- namic scene graphs for interactive object search with mobile manipulation.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Language-grounded dy- namic scene graphs for interactive object search with mobile manipulation

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.659802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.662617Z digest=sha256:267d80cf20b5b6641e863791fdb3bf14f24639ac8eb7a62330b7a44b927f3657

Observation 7f8c743e-8e18-49a9-a5be-c0849b5cd608 · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding 3d-llm: Injecting the 3d world into large language models

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.645097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.666931Z digest=sha256:f454370c31550221e4ab598001b82b79468db56253df60bef28d38b1a7b46bcd

Observation 683404d7-ed7d-4dac-adf6-8fb0919792a6 · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding 3d-llm: Injecting the 3d world into large language models

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.629183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.671068Z digest=sha256:ea9fd2a444d151ab1831c63810fa9cb6cb65976241fe1786769e8474c3d801d0

Observation 3d24ba0b-1302-4aee-9580-15a9882cb22d · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding LoRA: Low-Rank Adaptation of Large Language Models

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.674813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.674813Z digest=sha256:7ef0ed65da1bbda58fdf81b6ae67c3903d58e1396227ad0a6af2acd7031b863e

Observation f4b82864-43c3-4d00-96bb-a77d840c7f12 · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Chat-Scene: Bridging 3D Scene and Large Language Models with Object Identifiers

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.679239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.679239Z digest=sha256:d99c5c7971749626435fce99c53a1a6f665c4934f96fd892a0b4d9614dbdf613

Observation 0ba9728e-20fa-4e72-b32f-7596ebab974a · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Chat-scene: Bridging 3d scene and large language models with object identifiers

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.614451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.683973Z digest=sha256:6c0a87ea1e1c0bccd5a98305f5610f422134496d20a8887aad11ffe64331ddfc

Observation f417d8c4-095d-4ab4-8d5f-ecf7b5c5befb · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding An Embodied Generalist Agent in 3D World

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.688266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.688266Z digest=sha256:42416c1158d5b051e91ae40a823de881dfb3608ecc890c36a8a592690acf0f32

Observation 072329a4-5f28-4ef5-ba33-b29385f59046 · outbound

This paper cites Multi- view transformer for 3d visual grounding.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Multi- view transformer for 3d visual grounding

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.599564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.693229Z digest=sha256:3dc77de39fb040b195e0daeb47cdaa55a10b0f4c00b105c38d59b6a29188feed

Observation a0d10e22-e6cf-43a8-95a6-83dc76dd5eb0 · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Bottom up top down detection transform- ers for language grounding in images and point clouds

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.585779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.697585Z digest=sha256:a1088d7abae1073be9354508022c850ea624386fdd0692846f4e29d522ad10e3

Observation 34fe9717-9ee8-4306-a0a0-e047c4eff3c5 · outbound

This paper cites Image retrieval using scene graphs.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Image retrieval using scene graphs

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.571241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.702005Z digest=sha256:23147537e8a1a176e09634209df153b5eafe76123b3772bac0c5d169e1811928

Observation 3f473dbc-af2f-4174-9da4-4f3c3a33b941 · outbound

This paper cites Image gener- ation from scene graphs.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Image gener- ation from scene graphs

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.706163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.706163Z digest=sha256:1965379acdaab895f4212df08c801d1e8c4e9f2415f99d342046239639c61c92

Observation db1e78bc-60c0-448a-b6a0-59431af02a88 · outbound

This paper cites Robin3d: Improving 3d large language model via robust instruction tuning, 2025.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Robin3d: Improving 3d large language model via robust instruction tuning, 2025

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.547417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.710292Z digest=sha256:76d19e5c44cb30ba8bef3730f5ba156961ba4d86aedbcc44346f952c72324795

Observation be38b31b-7f5f-4bbb-ade6-951e2a89db15 · outbound

This paper cites Open3dsg: Open-vocabulary 3d scene graphs from point clouds with queryable objects and open-set relationships.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Open3dsg: Open-vocabulary 3d scene graphs from point clouds with queryable objects and open-set relationships

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.533147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.714517Z digest=sha256:ed5c54705c481c094cf9d1a70b4380b4caf9dc560d5d5022f84d74e8bc37197c

Observation 04df037a-6cf5-4664-85c8-49ae819d6e32 · outbound

This paper cites Oneformer3d: One transformer for unified point cloud segmentation.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Oneformer3d: One transformer for unified point cloud segmentation

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.519774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.718783Z digest=sha256:d51313a5a1a5b8f81ce1eeb6fe490b6a1bee63512d8b4fccb4e5ddf8ba05a268

Observation acc2e32b-094a-469e-bcd8-4b3f53ae7ba3 · outbound

This paper cites Beyond Bare Queries: Open-Vocabulary Object Grounding with 3D Scene Graph.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Beyond Bare Queries: Open-Vocabulary Object Grounding with 3D Scene Graph

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.723239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.723239Z digest=sha256:5f58d8b7557caeef1051a671e19bce69a743763a2e19bc493da6c501ed7f132a

Observation e8c46256-0ae8-43b0-aca2-222628685921 · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding SQA3D: Situated Question Answering in 3D Scenes

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.728239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.728239Z digest=sha256:c29bc59dfff2fa6f7081a6359f40066189f612d155f9f8660578d8b1e59231b4

Observation 877911a5-7369-479e-ad5d-484e8bed3566 · outbound

This paper cites Cross3dvg: Cross-dataset 3d visual grounding on different rgb-d scans.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Cross3dvg: Cross-dataset 3d visual grounding on different rgb-d scans

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.506206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.733025Z digest=sha256:0245343ea14bf81df6c242fa60249a688e3392513615388720474bf4b188f608

Observation ee896eaf-2925-48a2-a7c1-ca8be62be0a7 · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding DINOv2: Learning Robust Visual Features without Supervision

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.737469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.737469Z digest=sha256:f4263f0cc4b7f8655f8ca6ca2990db45d7237e2f08e0f104d9db57af9f05e1f3

Observation 9dd83c12-ffc4-41b8-9aba-b5a45b6e9ab9 · outbound

This paper cites Labrad-or: lightweight memory scene graphs for accurate bimodal reasoning in dynamic operating rooms.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Labrad-or: lightweight memory scene graphs for accurate bimodal reasoning in dynamic operating rooms

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.492689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.742117Z digest=sha256:32dc9db0d44af2ae6106afcf103c5f988ec9858b4ad33458fdab8e786bfe69bc

Observation 18a342d1-191c-4c5a-a01d-f027f3322237 · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Bleu: a method for automatic evaluation of machine translation

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.746409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.746409Z digest=sha256:cda4be655d650a2596c9a281aa59b33e60984e8fe49660d69ac0977a74cbe3c9

Observation 2f44d453-47cf-4529-8a1a-b5ec5817fd12 · outbound

This paper cites Scene graph semantic inference for im- age and text matching.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Scene graph semantic inference for im- age and text matching

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.471274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.751035Z digest=sha256:d89856e00811a5245183ae917a749ab04970174c87ce96b10427fd6dd48b1031

Observation 55649b9a-ee5c-4018-b571-68d2956c1c9e · outbound

This paper cites Openscene: 3d scene understanding with open vocabularies.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Openscene: 3d scene understanding with open vocabularies

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.457886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.755073Z digest=sha256:b0816aa3f23ab6dbf403f77e2235bfec93cdfe28c35e0a53849cd7c907c795be

Observation f891c3c1-02b5-43f4-8209-a10fbcddb0ae · outbound

This paper cites An approach to generate a caption for an image collection using scene graph generation.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding An approach to generate a caption for an image collection using scene graph generation

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.443988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.759071Z digest=sha256:3eae9b2241816cd402f0fa036929716ca0f8da0f8561bbf340c4b5061a62febd

Observation c0790fbe-6440-46f1-af69-0cda72d1d248 · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding GPT4Scene: Understand 3D Scenes from Videos with Vision-Language Models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.763185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.763185Z digest=sha256:54acfddbdf29b459e6966db1e8f852024c76e6ce7ea2cec94639c2f9ca184bd6

Observation d626c59c-7351-46e8-8028-3163af013edc · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Learning transferable visual models from natural language supervi- sion

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.767234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.767234Z digest=sha256:617c70ce01cde81a74a696b0b6286628a7e3e1014078e52b2f160a13f07e5a9e

Observation 16fe8780-03fa-4445-856e-ee3ba5b7a48e · outbound

This paper cites Kimera: From slam to spatial perception with 3d dynamic scene graphs.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Kimera: From slam to spatial perception with 3d dynamic scene graphs

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.421400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.771048Z digest=sha256:ef769f311618e12dc949092720c23909562bf15cd59f34621bb46ec4b1ffddba

Observation c544644e-c0e6-452d-afa3-5c06d998c2b3 · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Mask3d: Mask trans- former for 3d semantic instance segmentation

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.407337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.774692Z digest=sha256:6b902833694c08819a2f74108fde75ed87a4a895fd2801bb31c89d9d1605515f

Observation c60d792d-20c3-4b22-8297-6199b8d91547 · outbound

This paper cites Open- vocabulary object detection via scene graph discovery.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Open- vocabulary object detection via scene graph discovery

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.392943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.778238Z digest=sha256:d55df1eb64c956d274b9250937038f7919b837ce256b25ccb6d26d065d17d074

Observation bab9a9a3-8f8d-42bd-a350-db5f713a2d5c · outbound

This paper cites Attention is all you need.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Attention is all you need

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.782000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.782000Z digest=sha256:7f16b52c5b280e5b666b0590841468aee0a1fa3d1ce76542e8e0ce850cb4078f

Observation ffb34d65-30b7-4d95-a48a-9965967fcc3d · outbound

This paper cites Cider: Consensus-based image description evalu- ation.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Cider: Consensus-based image description evalu- ation

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.369921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.785773Z digest=sha256:81bc065ee545af1c48f404622e5855621da6bd265893d029bf7e386398b3ae93

Observation 5c7f83f5-633e-474c-8fa8-61a05f0c7ba8 · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Rio: 3d object instance re-localization in changing indoor environments

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.355930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.790000Z digest=sha256:ac1405357feda1d1098ac41c7df10b4b84d0ddb254a5d7cdf201564768b1ec7e

Observation 56fe7fc2-60b4-4e55-84f9-aab1752f577e · outbound

This paper cites Large Language Models for Robotics: Opportunities, Challenges, and Perspectives.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Large Language Models for Robotics: Opportunities, Challenges, and Perspectives

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.794731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.794731Z digest=sha256:996c12fb67154e00a62137f805c576161df0ee8ea430c1f5929c7601bf83589a

Observation 0725f1b8-8e72-4712-be62-c1dd4580d18b · outbound

This paper cites Vl-sat: Visual-linguistic semantics assisted training for 3d semantic scene graph prediction in point cloud.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Vl-sat: Visual-linguistic semantics assisted training for 3d semantic scene graph prediction in point cloud

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.342042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.800059Z digest=sha256:e7dfa0478dac964efc426654a4f1d3bff73fe949df56c174f7a2cda8374f286e

Observation bbd69f3e-4ae5-4171-a163-a936f9f7b235 · outbound

This paper cites Hierarchical open- vocabulary 3d scene graphs for language-grounded robot nav- igation.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Hierarchical open- vocabulary 3d scene graphs for language-grounded robot nav- igation

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.328152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.804220Z digest=sha256:fe9abc4fcdd1b5ed3f7150896daf63c79472f058c7573bcfb7369efa858350da

Observation 3e924966-e3d2-48c9-aa70-0cb2222d95e3 · outbound

This paper cites 3d question answering with scene graph reasoning.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding 3d question answering with scene graph reasoning

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.315282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.808122Z digest=sha256:5c872cdc806d27c51af09e0eece6c40e2673e98205cd8f8051792516a0b50058

Observation fc58e3e7-8e70-4514-a832-84203c3ccfdf · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Llm- grounder: Open-vocabulary 3d visual grounding with large language model as an agent

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.303029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.812085Z digest=sha256:b00ca5b6e331fdebac187a98f7461d8627e916c9d479ef22283d7094addd9982

Observation 223a03b8-d225-477f-a412-489bc62915c9 · outbound

This paper cites Cross-modal rela- tionship inference for grounding referring expressions.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Cross-modal rela- tionship inference for grounding referring expressions

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.290269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.815993Z digest=sha256:689117414afbc5ad47d9ad3a7e1cdcde6ccc06dd584822fb1747a13e51d8f5c7

Observation 30f473b7-5ed4-4462-97a0-81ccd005bb35 · outbound

This paper cites Auto-encoding scene graphs for image captioning.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Auto-encoding scene graphs for image captioning

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.278068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.820336Z digest=sha256:538b934da59e6155057d7219a5ea956cf9fa647ef8c7fab2df413c18dbc36c86

Observation f4665fc8-bf02-4b2b-ad39-59142f7493da · outbound

This paper cites Visual programming for zero- shot open-vocabulary 3d visual grounding.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Visual programming for zero- shot open-vocabulary 3d visual grounding

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.265623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.824633Z digest=sha256:149eae89ea7848efee5dcc11c97e1d245175b01c57fc8b7645a7d8c12049f77a

Observation 6b3a8ab3-60e3-40cf-b94e-301eaf70014d · outbound

This paper cites Com- monscenes: Generating commonsense 3d indoor scenes with scene graphs.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Com- monscenes: Generating commonsense 3d indoor scenes with scene graphs

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.251944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.829781Z digest=sha256:f8fa0ed16f3a7b54bb43c92402bfe8bee6524f4ab85265ece9e90b01c8d092ac

Observation 51dc88e6-7955-4359-96ba-684e104b9c40 · outbound

This paper cites Multi3drefer: Grounding text description to multiple 3d ob- jects.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Multi3drefer: Grounding text description to multiple 3d ob- jects

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.238189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.834111Z digest=sha256:568edcf7efb32cdaadd6cb0df7a3fe4dfd029fca0873a5295036311a531810c8

Observation 3800eaa6-e1f8-4f67-9d44-589457b2c39a · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding 3dvg- transformer: Relation modeling for visual grounding on point clouds

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.224050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.838365Z digest=sha256:31f8f4934d17951d00057a95b8c147e82f10b5e2ef4c3c43f78da75fba5015fb

Observation 669094e5-99c3-44a0-b803-63aa5363df9a · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Judging llm-as-a-judge with mt-bench and chatbot arena

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.209863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.842717Z digest=sha256:96a4c1f22120f8fee3e3d56e3bb7d7b3b364db57ffbbff6cc42ee15a3e30ef22

Observation 8976baea-efbc-42f6-8c4f-6ddb1a3455d0 · outbound

This paper cites Uni3D: Exploring Unified 3D Representation at Scale.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Uni3D: Exploring Unified 3D Representation at Scale

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-11T04:45:36.847073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:45:36.847073Z digest=sha256:77fdbf4654458fee01cd8ee666bc2eb833b98d37ff98f98f01f43a9b23e7ac7d

Observation 89fedc51-8929-4d71-baf7-bacc1d4e3e50 · outbound

This paper cites Opti- mal graph transformer viterbi knowledge inference network for more successful visual navigation.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding Opti- mal graph transformer viterbi knowledge inference network for more successful visual navigation

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.196100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.851944Z digest=sha256:17c8db78942af283fa2717b34c1ab34d4e3c2486de6d957d24b459bace20cee1

Observation 3ae8c7ab-2a96-41db-93de-e002efba6d37 · outbound

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

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding 3d-vista: Pre-trained transformer for 3d vision and text alignment

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.180461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.856211Z digest=sha256:769f2f4239bca0639c475ec12bcb96a774f55a85ce0d86e7687e1e83a42f08c2

Observation 06ea34ce-d823-42c0-97b6-b0aa9ba5fdf4 · outbound

This paper cites bath tub.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding bath tub

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.165858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.860555Z digest=sha256:0a192c8dc1b904551c1ac91c4ca1bf094cb8827b08e48993b5bd222e6e159daf

Observation 7cb05813-67e3-4ccc-aa5f-aee6fa2e87f3 · outbound

This paper cites It is sitting beside the tub.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding It is sitting beside the tub

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.152595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.865438Z digest=sha256:2dcbc1d99a67de6d3077cf5fac09f5f5f47ddd0dab058e58037894ea2b326d71

Observation cdd2b6d0-becb-44f3-8a07-78cf15afca1a · outbound

This paper cites It has a towel on top of the lid.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding It has a towel on top of the lid

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.139086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.869919Z digest=sha256:e6ad4545dff3103d44c68c6a04433406a462c5317149bd702844aabd4ce924c2

Observation cfba65d1-fe31-499a-9ad6-9e340927a428 · outbound

This paper cites There is a bathtub to the right of it and a counter to the left.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding There is a bathtub to the right of it and a counter to the left

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.125750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.874411Z digest=sha256:d9cba81d86afb4be7bdb61871365d214cea6dfd11dd87dbac4e8f6a3267fd8e4

Observation d6aa3c98-c211-4262-b323-96f3b41fd9d0 · outbound

This paper cites It is the only toilet in the room.

3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding It is the only toilet in the room

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T04:45:37.111401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T04:45:36.878751Z digest=sha256:21ed4f0b1931dd8e0e86ce39173775602b141cac43149a5b7da7328f40bcebae

Pith citing papers

Observation 1643fde7-2768-4b46-bc1c-8a6a60bbdb1c · inbound

Fast3D: Accelerating 3D Multi-modal Large Language Models for Efficient 3D Scene Understanding cites this paper.

Fast3D: Accelerating 3D Multi-modal Large Language Models for Efficient 3D Scene Understanding 3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-06T18:03:03.534576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:03:03.534576Z digest=sha256:498ed89508774472b6a88547f7460b53e40030f2465e60bc9772edd4b95e52d9

Observation c41d5265-a4aa-419d-ac1c-ac304ad5bd08 · inbound

Open-Vocabulary Indoor Object Grounding with 3D Hierarchical Scene Graph cites this paper.

Open-Vocabulary Indoor Object Grounding with 3D Hierarchical Scene Graph 3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T16:58:55.429664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:58:55.429664Z digest=sha256:dd3710ff40ebeb1dce688b3d500cb2bde3cbd36540fcd1cb1e058b0f37718e15

Observation 90527ecd-ee03-4b6f-b4cb-db007e119ec8 · inbound

CAIRN: Cross-Room 3D Scene Understanding with Topology-Aware Large Multimodal Models cites this paper.

CAIRN: Cross-Room 3D Scene Understanding with Topology-Aware Large Multimodal Models 3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding

Reference 60

Resolution
verified exact
local_arxiv, observed 2026-07-08T02:44:27.710353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-08T02:44:00.608590Z digest=sha256:3a8433df9faabcbb8d2d09ffb49b8f69600c21f03498ee364de97c70b9b4a390

Observation e1b60801-1547-4a74-9c20-7ce8b66a2a9a · inbound

CAIRN: Cross-Room 3D Scene Understanding with Topology-Aware Large Multimodal Models cites this paper.

CAIRN: Cross-Room 3D Scene Understanding with Topology-Aware Large Multimodal Models 3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding

Reference 60

Resolution
unresolved
no resolver link, observed 2026-07-14T16:00:13.133298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T16:00:13.133298Z digest=sha256:9467ea8b5810bfd71631260e17f076c58fe3dc7756938b3e2e7772d02a4da5c7