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Paper Citation Record · LEDGER

REGENT: A Retrieval-Augmented Generalist Agent That Can Act In-Context in New Environments

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2412.04759.

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

pith.paper-citation-record.v1
2412.04759 v2

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T18:51:36.003802Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:29:57.113471Z

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 d217f832-5e6c-455a-b125-f53f81695552 · inbound

MimicDroid: In-Context Learning for Humanoid Robot Manipulation from Human Play Videos cites this paper.

MimicDroid: In-Context Learning for Humanoid Robot Manipulation from Human Play Videos REGENT: A Retrieval-Augmented Generalist Agent That Can Act In-Context in New Environments

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-04T18:51:36.003802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T18:51:36.003802Z digest=sha256:efa0f414ac625c55615adc634309204b87f5064062b04c5c6c1f02b657339c25

Observation 22819cd7-768a-4f3f-a8bd-53e557346116 · inbound

Towards Scalable Multi-Task Reinforcement Learning with Large Decision Models cites this paper.

Towards Scalable Multi-Task Reinforcement Learning with Large Decision Models REGENT: A Retrieval-Augmented Generalist Agent That Can Act In-Context in New Environments

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-07-04T16:29:57.115152Z

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=pdf_text observed=2026-06-26T00:38:48.912290Z digest=sha256:1ca8ec538d155e054f38ba9573ead5bcbbac0de3d1545fb48140b7b2d3aa46b3