Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Modality Competition: What Makes Joint Training of Multi-modal Network Fail in Deep Learning? (Provably)
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2203.12221.
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 2026-08-11T14:44:43.980764Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
22
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 19eb69b2-bf4b-428f-807e-6f36a214aa05 · inbound
Discrepancy-Aware Attention Network for Enhanced Audio-Visual Zero-Shot Learning cites this paper.
Discrepancy-Aware Attention Network for Enhanced Audio-Visual Zero-Shot Learning Modality Competition: What Makes Joint Training of Multi-modal Network Fail in Deep Learning? (Provably)
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T14:44:43.980764Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cc42d244-99b0-408b-aa8e-dd18812ceefd · inbound
Optimizing Deep Learning Photometric Redshifts for the Roman Space Telescope with HST/CANDELS cites this paper.
Optimizing Deep Learning Photometric Redshifts for the Roman Space Telescope with HST/CANDELS Modality Competition: What Makes Joint Training of Multi-modal Network Fail in Deep Learning? (Provably)
Reference 85
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T02:27:08.975427Z
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 643cc06f-553f-4558-8bb6-ac5d9ecacc94 · inbound
Boosting Multimodal Federated Learning via Chained Modality Optimization cites this paper.
Boosting Multimodal Federated Learning via Chained Modality Optimization Modality Competition: What Makes Joint Training of Multi-modal Network Fail in Deep Learning? (Provably)
Reference 8
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-02T01:06:24.119228Z
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 0f9d909c-a5e4-4dc2-be78-7b5043a7f78e · inbound
Information-Theoretic Decomposition for Multimodal Interaction Learning cites this paper.
Information-Theoretic Decomposition for Multimodal Interaction Learning Modality Competition: What Makes Joint Training of Multi-modal Network Fail in Deep Learning? (Provably)
Reference 21
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T09:17:48.889696Z
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 c135ba4e-94fb-4030-bc3b-4208c9952154 · inbound
Foundation Models for Astrophysics cites this paper.
Foundation Models for Astrophysics Modality Competition: What Makes Joint Training of Multi-modal Network Fail in Deep Learning? (Provably)
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T04:31:48.795883Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.