Paper Citation Record · LEDGER

Tuning Large Multimodal Models for Videos using Reinforcement Learning from AI Feedback

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2402.03746.

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

pith.paper-citation-record.v1
2402.03746 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:51:25.225828Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T10:25:41.390707Z

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 6b7a964c-7182-4033-8d99-3d38e54cd72c · inbound

PPLLaVA: Varied Video Sequence Understanding With Prompt Guidance cites this paper.

PPLLaVA: Varied Video Sequence Understanding With Prompt Guidance Tuning Large Multimodal Models for Videos using Reinforcement Learning from AI Feedback

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-23T17:33:15.688660Z

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.

Observation 9fabc273-b5eb-4b28-a318-29c4073a9a0f · inbound

Unified Reward Model for Multimodal Understanding and Generation cites this paper.

Unified Reward Model for Multimodal Understanding and Generation Tuning Large Multimodal Models for Videos using Reinforcement Learning from AI Feedback

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-14T00:44:30.834901Z

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.

Observation f3996da9-09bb-4a8f-8bfb-570abc504414 · inbound

ReFoCUS: Reinforcement-guided Frame Optimization for Contextual Understanding cites this paper.

ReFoCUS: Reinforcement-guided Frame Optimization for Contextual Understanding Tuning Large Multimodal Models for Videos using Reinforcement Learning from AI Feedback

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T11:51:25.225828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2dd9dfb-5cdc-44c4-adae-5d950cc26882 · inbound

Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges cites this paper.

Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges Tuning Large Multimodal Models for Videos using Reinforcement Learning from AI Feedback

Reference 279

Resolution: unresolved; no resolver link, observed 2026-08-06T14:13:07.285336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 103c13cb-73d8-40a6-a73f-d54345f52c5c · inbound

VERTIGO: Visual Preference Optimization for Cinematic Camera Trajectory Generation cites this paper.

VERTIGO: Visual Preference Optimization for Cinematic Camera Trajectory Generation Tuning Large Multimodal Models for Videos using Reinforcement Learning from AI Feedback

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-13T21:18:17.198125Z

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.

Observation 4d28b137-a65e-400c-b13c-d8dd2b4b9be0 · inbound

No Place to Hide: Benchmarking Video Hallucination with Background-Controlled Pairs cites this paper.

No Place to Hide: Benchmarking Video Hallucination with Background-Controlled Pairs Tuning Large Multimodal Models for Videos using Reinforcement Learning from AI Feedback

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T10:25:41.391957Z

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.