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Paper Citation Record · LEDGER

SpatialBot: Precise Spatial Understanding with Vision Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 35 inbound Pith citation observations for arXiv:2406.13642.

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

pith.paper-citation-record.v1
2406.13642 v7

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 35 of 35 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:24:04.556539Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T16:18:37.306944Z

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0 of 0 outbound references displayed

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e251e3d7-f2cf-4e7b-a04c-63d90c83f091 · inbound

Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces cites this paper.

Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 10

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arxiv_id, observed 2026-05-22T09:27:44.172737Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-22T09:27:43.919941Z digest=sha256:b22ab585fd97f6b72bca2e05932a0f2313e705a8e705cc5eae0e3b6cecb3a927

Observation 7b406e20-d445-4681-a415-e8c4673aa066 · inbound

Can Multimodal Large Language Models Understand Spatial Relations? cites this paper.

Can Multimodal Large Language Models Understand Spatial Relations? SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 5

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source=arxiv_source observed=2026-08-07T14:24:04.556539Z digest=sha256:cf3cda99fc898bbcfec7a33d688a29702ce29c4ac076f16208ce33571748f835

Observation a02f28ca-6b43-4393-b617-ad0ba9419286 · inbound

Out of Sight, Not Out of Context? Egocentric Spatial Reasoning in VLMs Across Disjoint Frames cites this paper.

Out of Sight, Not Out of Context? Egocentric Spatial Reasoning in VLMs Across Disjoint Frames SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 4

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source=arxiv_source observed=2026-08-07T12:35:16.202407Z digest=sha256:b1eaa050adbaf6c1d59b303e3f47efbcd8f5077781ddda0f8526293b71c44f2b

Observation e726471f-2f61-4b87-ae35-606d52eb03d2 · inbound

A Spatial Relationship Aware Dataset for Robotics cites this paper.

A Spatial Relationship Aware Dataset for Robotics SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 1

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source=pdf_text observed=2026-08-07T00:51:24.318444Z digest=sha256:ca9c367400f265edaaff28fab612cdb4fab1d1459f631197632d762a03cd7125

Observation 64ec50b4-7244-4a6f-b574-b2061b2a6d40 · inbound

OscNet v1.5: Energy Efficient Hopfield Network on CMOS Oscillators for Image Classification cites this paper.

OscNet v1.5: Energy Efficient Hopfield Network on CMOS Oscillators for Image Classification SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 1

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source=pdf_text observed=2026-08-07T00:51:48.968184Z digest=sha256:c3e1f753b2041e155377ec9e541e72d377b87dabff624a32324291494b8f49b5

Observation ae73add2-f905-443d-b7aa-abbab6e06216 · inbound

ToSA: Token Merging with Spatial Awareness cites this paper.

ToSA: Token Merging with Spatial Awareness SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 15

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source=pdf_text observed=2026-08-06T23:01:29.887022Z digest=sha256:273c46bb3d1ae0424613e1b65c71f9fdaa642987c5ef95bcfec96ef21f7dfa8d

Observation 27c51cb1-594a-4ea0-9033-28489f4484f4 · inbound

Depth Anything at Any Condition cites this paper.

Depth Anything at Any Condition SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 11

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source=pdf_text observed=2026-08-06T20:52:02.423508Z digest=sha256:2847ca1a5b137d2507125d3f501b080a9da4c55ad9c04cf2ace7a5d68a5611a2

Observation 5404da64-bf32-4d31-9561-f7a31b58e557 · inbound

Ascending the Infinite Ladder: Benchmarking Spatial Deformation Reasoning in Vision-Language Models cites this paper.

Ascending the Infinite Ladder: Benchmarking Spatial Deformation Reasoning in Vision-Language Models SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 6

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source=pdf_text observed=2026-08-06T21:22:27.079986Z digest=sha256:f6050bc6c374e9b7e88fc48fa5488dc339c641236d25f6bd15a8319529528464

Observation c569df7c-8152-4629-8373-70c74568eca3 · inbound

BMMR: A Large-Scale Bilingual Multimodal Multi-Discipline Reasoning Dataset cites this paper.

BMMR: A Large-Scale Bilingual Multimodal Multi-Discipline Reasoning Dataset SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 47

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source=pdf_text observed=2026-08-06T20:15:52.733114Z digest=sha256:f3f1387bf2817d34bf9829d6f249d6e68882a296df1601d7bbbc5cb977e958b5

Observation dbb6d299-169c-4016-a284-3201659f70f7 · inbound

RwoR: Generating Robot Demonstrations from Human Hand Collection for Policy Learning without Robot cites this paper.

RwoR: Generating Robot Demonstrations from Human Hand Collection for Policy Learning without Robot SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 39

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source=pdf_text observed=2026-08-06T20:04:38.185326Z digest=sha256:c4fb6218a6bbd6a11ad9edff65516ee947436ebb2db13b0611a281f7ae045184

Observation 79ba07b9-c5b4-4f00-afe7-84d27c3f0500 · inbound

PRISM: Pointcloud Reintegrated Inference via Segmentation and Cross-attention for Manipulation cites this paper.

PRISM: Pointcloud Reintegrated Inference via Segmentation and Cross-attention for Manipulation SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 2

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source=pdf_text observed=2026-08-06T19:48:07.793262Z digest=sha256:2d29b1de6c4afc59a8104df6f8bd4a7e5f737cd6efe91bea068636004a7d03fe

Observation e2ed1f8c-2a8d-4720-84e0-5316589660b5 · inbound

Warehouse Spatial Question Answering with LLM Agent cites this paper.

Warehouse Spatial Question Answering with LLM Agent SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 1

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source=pdf_text observed=2026-08-06T17:29:38.536084Z digest=sha256:ead2995a036551f2d5ddebfd2856f27aec9f4734f51535e283ba87a61a00abc1

Observation 46a2075a-2a04-4750-af4a-544bd439c12c · inbound

Enhancing Spatial Reasoning in Vision-Language Models via Chain-of-Thought Prompting and Reinforcement Learning cites this paper.

Enhancing Spatial Reasoning in Vision-Language Models via Chain-of-Thought Prompting and Reinforcement Learning SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 33

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source=pdf_text observed=2026-08-06T19:54:48.156627Z digest=sha256:f1cd6f8bb3ef006750b4ee3fc82baccbc73605e993e4397f90e1691517443b1b

Observation 5957f5e9-d878-47cd-9323-840f7158ce10 · inbound

BenchDepth: Are We on the Right Way to Evaluate Depth Foundation Models? cites this paper.

BenchDepth: Are We on the Right Way to Evaluate Depth Foundation Models? SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 46

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source=pdf_text observed=2026-08-06T15:38:59.749275Z digest=sha256:6092e3a3b1a03530f1f77fccc235c7d5abd3edfb1141b5d8be4418a5bdf82b40

Observation 1cfeaa5f-2de8-42bf-b014-002bbc930982 · inbound

Canvas3D: Empowering Precise Spatial Control for Image Generation with Constraints from a 3D Virtual Canvas cites this paper.

Canvas3D: Empowering Precise Spatial Control for Image Generation with Constraints from a 3D Virtual Canvas SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 7

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source=pdf_text observed=2026-08-05T22:23:09.481651Z digest=sha256:4d58d7a31aecb9791b6cab2eb7cd9d403762f1c4c46dca9a9ebfd4e293187260

Observation 452ba9fc-3031-4cb0-aa31-3c394b634645 · inbound

Embodied-R1: Reinforced Embodied Reasoning for General Robotic Manipulation cites this paper.

Embodied-R1: Reinforced Embodied Reasoning for General Robotic Manipulation SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 2

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arxiv_id, observed 2026-05-18T22:06:51.720215Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T22:04:34.235731Z digest=sha256:dff6e49eb446aedc65dde2363eaeb691938f2e4d1ed54adc3db63c9a70d04ad3

Observation 69047047-b5e5-45cd-8174-14a6659374bd · inbound

Understanding Space Is Rocket Science -- Only Top Reasoning Models Can Solve Spatial Understanding Tasks cites this paper.

Understanding Space Is Rocket Science -- Only Top Reasoning Models Can Solve Spatial Understanding Tasks SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 10

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Observation 82cd167f-a1ad-452d-a6d8-9646c13e431c · inbound

GAE: Unleashing Physical Potential of VLM with Generalizable Action Expert cites this paper.

GAE: Unleashing Physical Potential of VLM with Generalizable Action Expert SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 7

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source=arxiv_source observed=2026-08-04T11:38:11.546062Z digest=sha256:e8f440b192b2daaa484413574e16fd23a6f6cef0d8dbaaafcf97903d1ac30e89

Observation a73e99a7-7552-4f1a-9e21-59d69faf6d4b · inbound

SlotVLA: Towards Modeling of Object-Relation Representations in Robotic Manipulation cites this paper.

SlotVLA: Towards Modeling of Object-Relation Representations in Robotic Manipulation SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 16

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arxiv_id, observed 2026-05-18T00:25:32.994831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T00:22:41.611893Z digest=sha256:29ee31210df3ba74857d15f727010cf94a1e79df6c46f2582fd3285b501a4380

Observation c89204c0-a66f-433b-9146-90382ced24ee · inbound

SpatialThinker: Reinforcing Scene Graph-Grounded Spatial Reasoning via Dense Rewards cites this paper.

SpatialThinker: Reinforcing Scene Graph-Grounded Spatial Reasoning via Dense Rewards SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 2

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no resolver link, observed 2026-08-03T23:08:49.001243Z

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source=pdf_text observed=2026-08-03T23:08:49.001243Z digest=sha256:ee009de9f98fe5eafae741dbe503d507e183395842e612ee812005486da68d42

Observation f4991661-264f-47e3-b6ef-96f837d1bf93 · inbound

SPEAR-1: Scaling Beyond Robot Demonstrations via 3D Understanding cites this paper.

SPEAR-1: Scaling Beyond Robot Demonstrations via 3D Understanding SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 7

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arxiv_id, observed 2026-05-17T20:22:04.620503Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 89fc6ba7-bae3-419e-9de8-09a4738a8d4a · inbound

MonoSR: Open-Vocabulary Spatial Reasoning from Monocular Images cites this paper.

MonoSR: Open-Vocabulary Spatial Reasoning from Monocular Images SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 7

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Observation 0a578d09-6ef1-47c0-acc8-fb7471255bc4 · inbound

Spatio-Temporal Grounding of Large Language Models from Perception Streams cites this paper.

Spatio-Temporal Grounding of Large Language Models from Perception Streams SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 4

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arxiv_id, observed 2026-05-11T07:26:02.678079Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 64bbe8e8-686b-4ab3-8c2a-8a9ecec42f57 · inbound

EmbodiedMidtrain: Bridging the Gap between Vision-Language Models and Vision-Language-Action Models via Mid-training cites this paper.

EmbodiedMidtrain: Bridging the Gap between Vision-Language Models and Vision-Language-Action Models via Mid-training SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 4

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arxiv_id, observed 2026-05-11T13:11:03.815073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 54209770-f05e-4e37-ba5e-3fc297cfd849 · inbound

4DThinker: Thinking with 4D Imagery for Dynamic Spatial Understanding cites this paper.

4DThinker: Thinking with 4D Imagery for Dynamic Spatial Understanding SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 2

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arxiv_id, observed 2026-05-11T18:41:11.692955Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation fa29e92c-af28-48a0-a4ed-1caaaf27aa2f · inbound

4DThinker: Thinking with 4D Imagery for Dynamic Spatial Understanding cites this paper.

4DThinker: Thinking with 4D Imagery for Dynamic Spatial Understanding SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 2

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arxiv_id, observed 2026-05-25T06:16:39.992535Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-25T06:15:33.062980Z digest=sha256:b569c6e2ca2839a6099a12f01ca0aee7f124a86f0fd6dc80e73b2abb916e42c5

Observation 9aa7b8c5-3f88-49ab-bdd7-ffe4c9f2a117 · inbound

Thinking with Novel Views: A Systematic Analysis of Generative-Augmented Spatial Intelligence cites this paper.

Thinking with Novel Views: A Systematic Analysis of Generative-Augmented Spatial Intelligence SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 4

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arxiv_id, observed 2026-05-12T03:26:19.382386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 88753f51-bdb3-4f4a-892d-3971c0915305 · inbound

ESI-Bench: Towards Embodied Spatial Intelligence that Closes the Perception-Action Loop cites this paper.

ESI-Bench: Towards Embodied Spatial Intelligence that Closes the Perception-Action Loop SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 1

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arxiv_id, observed 2026-05-20T10:53:13.222326Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation b0018adf-4f46-4670-9535-fda813036c2d · inbound

ESI-Bench: Towards Embodied Spatial Intelligence that Closes the Perception-Action Loop cites this paper.

ESI-Bench: Towards Embodied Spatial Intelligence that Closes the Perception-Action Loop SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 1

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arxiv_id, observed 2026-07-01T15:05:47.182481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T18:25:17.831116Z digest=sha256:8ddf98d8bb8c10af4a8f0ed8c028d65c14492b5b483014d86069400445615afa

Observation 016b2ce0-c946-4469-add7-ec1b9b10e22c · inbound

LLaVA-OneVision-2: Towards Next-Generation Perceptual Intelligence cites this paper.

LLaVA-OneVision-2: Towards Next-Generation Perceptual Intelligence SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 6

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arxiv_id, observed 2026-06-29T22:13:59.560592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-29T22:12:05.365596Z digest=sha256:2b5dabeede9ef918f304dea4a7bbf8c04200733cef3554d177ddca5e03687ef4

Observation effb4d79-bfe3-4ed5-b356-8d1378a6ecba · inbound

VLM3: Vision Language Models Are Native 3D Learners cites this paper.

VLM3: Vision Language Models Are Native 3D Learners SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 3

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arxiv_id, observed 2026-06-29T07:53:14.019914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-29T07:45:31.978215Z digest=sha256:e2f3284e4063b49a0cb80349504f641b993fcf04a30544326abc81f62dc1d765

Observation 6f97f28b-55ff-41db-b7ee-b719312b5659 · inbound

Brick-Composer: Using MLLMs for Assembly with Diverse Bricks cites this paper.

Brick-Composer: Using MLLMs for Assembly with Diverse Bricks SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 1

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metadata mismatch
arxiv_id, observed 2026-07-02T08:26:48.424339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T05:59:29.302038Z digest=sha256:b2b1ade405cc4a73c2d095fc194b374ab7046c6e1b0867d79c71942f2d6ef6f6

Observation 443ec8bd-ee16-464b-b4fb-1deb9e64acf5 · inbound

Decodable Is Not Grounded: A Vision-Ablation Arbiter for VLM Spatial Reasoning cites this paper.

Decodable Is Not Grounded: A Vision-Ablation Arbiter for VLM Spatial Reasoning SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 6

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arxiv_id, observed 2026-07-01T09:35:41.110274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-07-01T06:23:00.372251Z digest=sha256:a3e7a3df3e8a3c927fd815df40da706e50b7a905f9004531413f27fc24448bee

Observation bb376c85-f6f5-470b-b01f-51d3b0834949 · inbound

SpaceEra++: A Unified Framework Towards 3D Spatial Reasoning in Video cites this paper.

SpaceEra++: A Unified Framework Towards 3D Spatial Reasoning in Video SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 10

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arxiv_id, observed 2026-07-03T16:18:37.308596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-07-03T16:16:41.412451Z digest=sha256:079edaee4a58d2f5b2e61041fab9ec99567d42f7590e4b90235ec91afa451eec

Observation 83309848-96fa-4915-a231-5899935daab2 · inbound

When Memory Lies: An Empirical Study of Spatial Memory Staleness in VLM Agents cites this paper.

When Memory Lies: An Empirical Study of Spatial Memory Staleness in VLM Agents SpatialBot: Precise Spatial Understanding with Vision Language Models

Reference 18

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source=arxiv_source observed=2026-08-06T21:49:20.587662Z digest=sha256:cdf8811d9174da57be8b8f4ff6219eb920f8b539a56e17b3ef5bf951c1234fe1