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Paper Citation Record · LEDGER

Self-Captioning Multimodal Interaction Tuning: Amplifying Exploitable Redundancies for Robust Vision Language Models

As of 15 July 2026, this Paper Citation Record lists 4 of 4 outbound references and 0 inbound Pith citation observations for arXiv:2605.08145.

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

pith.paper-citation-record.v1
2605.08145 v2

Coverage vector

measured 4 of 4 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-01T00:26:29.184569Z

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-14T06:31:01.685423+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

4 of 4 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 51ffdc65-4ee6-4186-8488-8565efd9fb9c · outbound

This paper cites URL https: //proceedings.neurips.cc/paper_files /paper/2024/file/ed45d6a03de84cc650c ae0655f699356-Paper-Conference.pdf.

Self-Captioning Multimodal Interaction Tuning: Amplifying Exploitable Redundancies for Robust Vision Language Models URL https: //proceedings.neurips.cc/paper_files /paper/2024/file/ed45d6a03de84cc650c ae0655f699356-Paper-Conference.pdf

Reference 1

Resolution
verified exact
doi, observed 2026-07-01T00:35:10.023648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.

source=pdf_text observed=2026-07-01T00:26:29.184569Z digest=sha256:b91b8574c5d7a56c8a4561875d47853f3170debd9f57526ea87fbd649d96faf2

Observation f2eb8e6f-78e9-4b07-bcbf-88bd18c1cc29 · outbound

This paper cites Entropy , author =.

Self-Captioning Multimodal Interaction Tuning: Amplifying Exploitable Redundancies for Robust Vision Language Models Entropy , author =

Reference 2

Resolution
metadata mismatch
doi, observed 2026-07-01T00:35:10.017291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.

source=pdf_text observed=2026-07-01T00:26:29.184569Z digest=sha256:85fb4ced835c8810c2b7f65a8aa9c58610eb8ff96ec8ed057827b4ff79799507

Observation f23c1006-f460-4cbf-9ea7-8f8526a6570b · outbound

This paper cites Entropy , author =.

Self-Captioning Multimodal Interaction Tuning: Amplifying Exploitable Redundancies for Robust Vision Language Models Entropy , author =

Reference 3

Resolution
metadata mismatch
doi, observed 2026-07-01T00:35:10.021529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.

source=pdf_text observed=2026-07-01T00:26:29.184569Z digest=sha256:05956ca458eb702c0ffe3f3d3490a62bad3d6cda3605bd6cca95a696e3d8b7d1

Observation f345a0b5-f0e6-478c-93d1-15a6d375ce25 · outbound

This paper cites Does Object Grounding Really Reduce Hallucination of Large Vision-Language Models?.

Self-Captioning Multimodal Interaction Tuning: Amplifying Exploitable Redundancies for Robust Vision Language Models Does Object Grounding Really Reduce Hallucination of Large Vision-Language Models?

Reference 4

Resolution
verified exact
doi, observed 2026-07-01T00:35:10.019438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.

source=pdf_text observed=2026-07-01T00:26:29.184569Z digest=sha256:27ccb53827237649357a420452ebe270727a5d21ca0d0ff1cf849219c6f9e2b5

Pith citing papers

No inbound Pith citation observations are available.