Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Text-Only Training for Image Captioning using Noise-Injected CLIP
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2211.00575.
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 2026-08-07T04:29:23.701411Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T04:55:23.983995Z
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 09055feb-c934-45bb-b5b2-a5b9304eaafe · inbound
Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning cites this paper.
Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning Text-Only Training for Image Captioning using Noise-Injected CLIP
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:29:23.701411Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 00a9a893-7320-4bb5-884a-67d9c6c1167c · inbound
MoMa: Modulating Mamba for Adapting Image Foundation Models to Video Recognition cites this paper.
MoMa: Modulating Mamba for Adapting Image Foundation Models to Video Recognition Text-Only Training for Image Captioning using Noise-Injected CLIP
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:51:55.746646Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c8e3154c-0770-4be3-9f31-d75c9ecab9e0 · inbound
Modality Gap-Driven Subspace Alignment Training Paradigm For Multimodal Large Language Models cites this paper.
Modality Gap-Driven Subspace Alignment Training Paradigm For Multimodal Large Language Models Text-Only Training for Image Captioning using Noise-Injected CLIP
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T08:17:36.066278Z
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 0e6a904c-6801-4af9-a36f-b62e22c7ec4a · inbound
Modality Gap-Driven Subspace Alignment Training Paradigm For Multimodal Large Language Models cites this paper.
Modality Gap-Driven Subspace Alignment Training Paradigm For Multimodal Large Language Models Text-Only Training for Image Captioning using Noise-Injected CLIP
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T05:34:28.659477Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d641bb7a-ff3d-4379-8ba9-ffb19b54360d · inbound
Understanding and Improving Noisy Embedding Techniques in Instruction Finetuning cites this paper.
Understanding and Improving Noisy Embedding Techniques in Instruction Finetuning Text-Only Training for Image Captioning using Noise-Injected CLIP
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T04:55:23.988089Z
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.