Paper Citation Record · LEDGER

Text-Only Training for Image Captioning using Noise-Injected CLIP

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2211.00575.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2211.00575 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:10:17.456353Z

measured 0 of 1 external citation measurements

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 425d1255-1895-4219-bb4c-41052895f79c · inbound

DistinctAD: Distinctive Audio Description Generation in Contexts cites this paper.

DistinctAD: Distinctive Audio Description Generation in Contexts Text-Only Training for Image Captioning using Noise-Injected CLIP

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-12T11:30:20.298071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 295e36b9-0db3-4fc6-8ef7-a83019bf49f5 · inbound

How Vision-Language Tasks Benefit from Large Pre-trained Models: A Survey cites this paper.

How Vision-Language Tasks Benefit from Large Pre-trained Models: A Survey Text-Only Training for Image Captioning using Noise-Injected CLIP

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-11T18:11:54.516711Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c234e2e3-f111-43a0-a2e4-2940865c31d8 · inbound

Improving Image Captioning by Mimicking Human Reformulation Feedback at Inference-time cites this paper.

Improving Image Captioning by Mimicking Human Reformulation Feedback at Inference-time Text-Only Training for Image Captioning using Noise-Injected CLIP

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T21:34:51.196979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+00:00.

Observation a9dfdb99-f0a2-475d-b9ba-b17f6bc85d72 · inbound

Watching Synthetic Videos: Aligning Cross-modal Representations with Visual Synthesis for Zero-shot Video Captioning cites this paper.

Watching Synthetic Videos: Aligning Cross-modal Representations with Visual Synthesis for Zero-shot Video Captioning Text-Only Training for Image Captioning using Noise-Injected CLIP

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T12:10:17.456353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.