Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
$\gamma-$MoD: Exploring Mixture-of-Depth Adaptation for Multimodal Large Language Models
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2410.13859.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:09:06.707034Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T11:28:04.112709Z
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 da8c2a85-2051-4c3e-bb92-342941a2ceda · inbound
EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models cites this paper.
EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models $\gamma-$MoD: Exploring Mixture-of-Depth Adaptation for Multimodal Large Language Models
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:09:06.707034Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 36ae3d76-ac42-49bb-95f1-76b92fa6fc76 · inbound
Short-LVLM: Compressing and Accelerating Large Vision-Language Models by Pruning Redundant Layers cites this paper.
Short-LVLM: Compressing and Accelerating Large Vision-Language Models by Pruning Redundant Layers $\gamma-$MoD: Exploring Mixture-of-Depth Adaptation for Multimodal Large Language Models
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T10:55:18.235792Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b7ce8b3d-8718-407d-8c98-81f3c5e60282 · inbound
CogVLA: Cognition-Aligned Vision-Language-Action Model via Instruction-Driven Routing & Sparsification cites this paper.
CogVLA: Cognition-Aligned Vision-Language-Action Model via Instruction-Driven Routing & Sparsification $\gamma-$MoD: Exploring Mixture-of-Depth Adaptation for Multimodal Large Language Models
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:42:32.714770Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0b129038-92bb-43d3-88fe-e996aa119f4f · inbound
Tackling Multimodal Learning Challenges with Mixture-of-Expert: A Survey cites this paper.
Tackling Multimodal Learning Challenges with Mixture-of-Expert: A Survey $\gamma-$MoD: Exploring Mixture-of-Depth Adaptation for Multimodal Large Language Models
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T15:34:48.309533Z
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.
Observation f4609a6d-3840-4216-b3ea-012d5075f0ca · inbound
Reroute, Don't Remove: Recoverable Visual Token Routing for Vision-Language Models cites this paper.
Reroute, Don't Remove: Recoverable Visual Token Routing for Vision-Language Models $\gamma-$MoD: Exploring Mixture-of-Depth Adaptation for Multimodal Large Language Models
Reference 51
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T11:28:04.114374Z
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.