Paper Citation Record · LEDGER

AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning

As of 10 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 1 inbound Pith citation observation for arXiv:2605.24816.

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

pith.paper-citation-record.v1
2605.24816 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T12:22:17.966775Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T16:08:01.984050Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

14 of 14 outbound references displayed

verified exact5
verified fuzzy5
unresolved1
parse uncertain0
malformed identifier1
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fd93b306-4bac-4f9e-96b4-641e07cc7e60 · outbound

This paper cites Gated Multimodal Units for Information Fusion.

AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning Gated Multimodal Units for Information Fusion

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-06-30T12:24:39.650988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e20b191b-5c0c-42f8-88bf-49ec5a734d44 · outbound

This paper cites Qwen3-VL Technical Report.

AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning Qwen3-VL Technical Report

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-06-30T12:24:39.654944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 56b17ac2-220c-42be-bf87-8582aa38ae7d · outbound

This paper cites InProceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2(Toronto ON, Canada)(KDD ’25).

AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning InProceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2(Toronto ON, Canada)(KDD ’25)

Reference 3

Resolution: metadata mismatch; doi, observed 2026-06-30T12:24:38.230816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2de76ff4-7b81-4aad-aef9-dfc3257ce928 · outbound

This paper cites Understanding and Mitigating Miscalibration in Prompt Tuning for Vision-Language Models.

AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning Understanding and Mitigating Miscalibration in Prompt Tuning for Vision-Language Models

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T12:24:39.658075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ed832ff8-8391-4b84-8325-7db04f848307 · outbound

This paper cites Deep Multimodal Learning with Missing Modality: A Survey.

AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning Deep Multimodal Learning with Missing Modality: A Survey

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-06-30T12:24:39.660691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation edb21d6f-f6c9-4de3-abf0-d2bb78f844e6 · outbound

This paper cites Prompting through Prototype: A Prototype-based Prompt Learning on Pretrained Vision-Language Models.

AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning Prompting through Prototype: A Prototype-based Prompt Learning on Pretrained Vision-Language Models

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-06-30T12:24:39.664089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4e2d63dd-6222-49b2-bdd5-534cdb5e25a2 · outbound

This paper cites Implementation of AOEPT on Dual-Stream Multimodal Transformer In the main paper, we present the mathematical formulation of AOEPT on the single-stream MT for clarity.

AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning Implementation of AOEPT on Dual-Stream Multimodal Transformer In the main paper, we present the mathematical formulation of AOEPT on the single-stream MT for clarity

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T06:16:02.520194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 637e1911-cfbf-45b0-b9ba-16c0473f5ae2 · outbound

This paper cites benign confounders.

AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning benign confounders

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T06:16:02.511837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c2d90547-0ed0-4aca-91e8-5eed217c1a22 · outbound

This paper cites Moreover, we also adopt a tri-modal MT backbone ❸ MulT(Tsai et al.,.

AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning Moreover, we also adopt a tri-modal MT backbone ❸ MulT(Tsai et al.,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T06:16:02.513944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7d775cbc-c6b2-4c32-9a67-5e34abdca560 · outbound

This paper cites Below, we provide a detailed implementation the backbones: ▷ CLIP:For CLIP, we adopt the pretrained ViT-B/16 variant following prior studies (Hu et al., 2024).

AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning Below, we provide a detailed implementation the backbones: ▷ CLIP:For CLIP, we adopt the pretrained ViT-B/16 variant following prior studies (Hu et al., 2024)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T06:16:02.517633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ccc9104b-ad54-4c33-9867-5b165d2f692e · outbound

This paper cites an unresolved cited work.

AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning Unresolved cited work

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-06-30T12:24:39.646549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 394db72e-ee1e-490e-9280-a88613804607 · outbound

This paper cites Following prior studies (Hu et al., 2024), we insert all type of MCPs into each sample.

AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning Following prior studies (Hu et al., 2024), we insert all type of MCPs into each sample

Reference 12

Resolution: malformed identifier; raw_fallback, observed 2026-07-09T06:16:02.524949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 98bdc282-9240-4e18-b0d8-c4d2a6f5bcc0 · outbound

This paper cites As illustrated in Table 8, AOEPT outperforms all baselines across all missing settings.

AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning As illustrated in Table 8, AOEPT outperforms all baselines across all missing settings

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T06:16:02.522517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bca7ac49-ae10-4ebe-a562-dfb433473d78 · outbound

This paper cites an unresolved cited work.

AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-07-09T06:16:02.526865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

Observation 5c267f9b-9961-425c-99b9-6d86e211cd88 · inbound

OC-Distill: Ontology-aware Contrastive Learning with Cross-Modal Distillation for ICU Risk Prediction cites this paper.

OC-Distill: Ontology-aware Contrastive Learning with Cross-Modal Distillation for ICU Risk Prediction AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning

Reference 2026

Resolution: unresolved; no resolver link, observed 2026-08-02T16:08:01.984050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.