Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
An Empirical Analysis on Spatial Reasoning Capabilities of Large Multimodal Models
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2411.06048.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:36:21.486935Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T08:59:43.214652Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation a4532fb0-a63d-47eb-bfe9-83c99d75f682 · inbound
Seeing is Not Reasoning: MVPBench for Graph-based Evaluation of Multi-path Visual Physical CoT cites this paper.
Seeing is Not Reasoning: MVPBench for Graph-based Evaluation of Multi-path Visual Physical CoT An Empirical Analysis on Spatial Reasoning Capabilities of Large Multimodal Models
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:36:21.486935Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0ea5f7f5-25b9-4990-8352-8fe4af0d8431 · inbound
BYO-Eval: Build Your Own Dataset for Fine-Grained Visual Assessment of Multimodal Language Models cites this paper.
BYO-Eval: Build Your Own Dataset for Fine-Grained Visual Assessment of Multimodal Language Models An Empirical Analysis on Spatial Reasoning Capabilities of Large Multimodal Models
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T10:35:44.119016Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 808c1182-1559-48a7-9ae8-1d9e524267d3 · inbound
Scene Graph-Guided Proactive Replanning for Failure-Resilient Embodied Agent cites this paper.
Scene Graph-Guided Proactive Replanning for Failure-Resilient Embodied Agent An Empirical Analysis on Spatial Reasoning Capabilities of Large Multimodal Models
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T20:05:11.542674Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 46dbd422-b89c-465a-9b0e-083c1660ed6d · 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 An Empirical Analysis on Spatial Reasoning Capabilities of Large Multimodal Models
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T11:56:10.891255Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a7cc2200-ebc5-4511-99e4-6835ecd51d87 · inbound
Lost in Space? Vision-Language Models Struggle with Relative Camera Pose Estimation cites this paper.
Lost in Space? Vision-Language Models Struggle with Relative Camera Pose Estimation An Empirical Analysis on Spatial Reasoning Capabilities of Large Multimodal Models
Reference 5
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-16T09:32:41.257423Z
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.
Observation 5f297558-ecb7-4ad9-bcb3-84ee7ac68369 · inbound
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving cites this paper.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving An Empirical Analysis on Spatial Reasoning Capabilities of Large Multimodal Models
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T05:15:22.851937Z
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.
Observation 7713b246-3966-4641-94a6-a2f2fbcaf864 · inbound
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving cites this paper.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving An Empirical Analysis on Spatial Reasoning Capabilities of Large Multimodal Models
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.119897Z
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.
Observation 32acffc1-56cd-4951-b4ab-fea1bc481b29 · inbound
Causal Scaffolding for Physical Reasoning: A Benchmark for Causally-Informed Physical World Understanding in VLMs cites this paper.
Causal Scaffolding for Physical Reasoning: A Benchmark for Causally-Informed Physical World Understanding in VLMs An Empirical Analysis on Spatial Reasoning Capabilities of Large Multimodal Models
Reference 51
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T15:57:06.724349Z
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.
Observation 89cd86ee-d8f7-42e1-935f-66d52f2fb152 · inbound
SATURN: Symbolic Spatial Reasoning for Multi-Perspective Grounding cites this paper.
SATURN: Symbolic Spatial Reasoning for Multi-Perspective Grounding An Empirical Analysis on Spatial Reasoning Capabilities of Large Multimodal Models
Reference 5
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-04T08:59:43.216159Z
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.