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Paper Citation Record · LEDGER

Improving Multimodal Interactive Agents with Reinforcement Learning from Human Feedback

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2211.11602.

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

pith.paper-citation-record.v1
2211.11602 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:18:22.770620Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T04:32:33.097962Z

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 f0c690ad-23e6-4581-9afe-d75e29c970d6 · inbound

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning cites this paper.

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning Improving Multimodal Interactive Agents with Reinforcement Learning from Human Feedback

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-23T04:32:33.101236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-23T04:30:38.804702Z digest=sha256:896df58c63df36a98b1c9b1fe635b0b65687899f21559861f37cdee94040d10a

Observation f65e64b5-3d56-4455-a2bc-a2f382acbf3d · inbound

Conditional Multi-Stage Failure Recovery for Embodied Agents cites this paper.

Conditional Multi-Stage Failure Recovery for Embodied Agents Improving Multimodal Interactive Agents with Reinforcement Learning from Human Feedback

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T19:18:22.770620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:18:22.770620Z digest=sha256:54f7f124867d29dcf0225feb0564d1889a8b2452c4f7ceeb1729f58cd1cd202a