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Paper Citation Record · LEDGER

Multi-modal Preference Alignment Remedies Degradation of Visual Instruction Tuning on Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2402.10884.

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

pith.paper-citation-record.v1
2402.10884 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T12:27:27.384681Z

measured 1 of 1 external citation measurements

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

15
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 c33c94a5-eab8-4461-85ea-8c3b8f5d4bc2 · inbound

Improving Large Vision and Language Models by Learning from a Panel of Peers cites this paper.

Improving Large Vision and Language Models by Learning from a Panel of Peers Multi-modal Preference Alignment Remedies Degradation of Visual Instruction Tuning on Language Models

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-05T12:27:27.384681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:27:27.384681Z digest=sha256:72770b6ab03c1a0dd3ef8476b7e01fef18033202f301d92758a25d4041ec5789

Observation def2756e-fb6b-4dbf-80f7-2d4dd0aba576 · inbound

Deep Pre-Alignment for VLMs cites this paper.

Deep Pre-Alignment for VLMs Multi-modal Preference Alignment Remedies Degradation of Visual Instruction Tuning on Language Models

Reference 113

Resolution
verified exact
arxiv_id, observed 2026-05-19T16:27:39.142833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-19T16:26:41.094936Z digest=sha256:51c11d2a7044a4e10d460bc41a889b7a6a97ac4aa0e35b0a6018ecdf5e4a3768

Observation ca8b56b7-8418-4206-bded-76ad1d6b4aff · inbound

A Nash Equilibrium Framework For Training-Free Multimodal Step Verification cites this paper.

A Nash Equilibrium Framework For Training-Free Multimodal Step Verification Multi-modal Preference Alignment Remedies Degradation of Visual Instruction Tuning on Language Models

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-20T06:13:05.287776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-20T06:10:36.290559Z digest=sha256:5d5b25d9f705c6718f849ad2d503d4f05b2f9e29fb9e69703a0a5fdd809819f7