Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MM-SHAP: A Performance-agnostic Metric for Measuring Multimodal Contributions in Vision and Language Models & Tasks
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2212.08158.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T20:15:40.156886Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-19T00:36:56.286917Z
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 2d5f2421-39f7-46c1-b6b2-1cdbd4dd4215 · inbound
Mantis Shrimp: Exploring Photometric Band Utilization in Computer Vision Networks for Photometric Redshift Estimation cites this paper.
Mantis Shrimp: Exploring Photometric Band Utilization in Computer Vision Networks for Photometric Redshift Estimation MM-SHAP: A Performance-agnostic Metric for Measuring Multimodal Contributions in Vision and Language Models & Tasks
Reference 101
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:15:40.156886Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7dad1d93-067b-43bb-95be-4acf1461e606 · inbound
On the Risk of Misleading Reports: Diagnosing Textual Biases in Multimodal Clinical AI cites this paper.
On the Risk of Misleading Reports: Diagnosing Textual Biases in Multimodal Clinical AI MM-SHAP: A Performance-agnostic Metric for Measuring Multimodal Contributions in Vision and Language Models & Tasks
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T10:22:23.218640Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 15efebfc-e075-42e7-b6b5-039421b0f310 · inbound
Decoding the Multimodal Maze: A Systematic Review on the Adoption of Explainability in Multimodal Attention-based Models cites this paper.
Decoding the Multimodal Maze: A Systematic Review on the Adoption of Explainability in Multimodal Attention-based Models MM-SHAP: A Performance-agnostic Metric for Measuring Multimodal Contributions in Vision and Language Models & Tasks
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T00:36:56.288779Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 983952dd-0f12-46e1-ab15-945fc4349f04 · inbound
Decoding the Multimodal Maze: A Systematic Review on the Adoption of Explainability in Multimodal Attention-based Models cites this paper.
Decoding the Multimodal Maze: A Systematic Review on the Adoption of Explainability in Multimodal Attention-based Models MM-SHAP: A Performance-agnostic Metric for Measuring Multimodal Contributions in Vision and Language Models & Tasks
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T00:02:58.614148Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.