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Paper Citation Record · LEDGER

Guiding Policies with Language via Meta-Learning

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1811.07882.

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

pith.paper-citation-record.v1
1811.07882 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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:26:30.441600Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T21:17:44.749200Z

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 856a9f52-b455-426d-a4fd-1a7d06d0c128 · inbound

Mastering emergent language: learning to guide in simulated navigation cites this paper.

Mastering emergent language: learning to guide in simulated navigation Guiding Policies with Language via Meta-Learning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-14T13:26:30.441600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:26:30.441600Z digest=sha256:c4cac729b0c6b7db9425813b163ce157a98dc5ee35cade9fdfe1ec1b50fef396

Observation d6c92161-96ed-4fca-a17e-2ff388fe2eaf · inbound

Residual Reward Models for Preference-based Reinforcement Learning cites this paper.

Residual Reward Models for Preference-based Reinforcement Learning Guiding Policies with Language via Meta-Learning

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-08-06T21:17:44.845297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T21:17:37.863655Z digest=sha256:2fd6729c995a7fd6b365c542e59dd5c901e1b176530d6b8950d9986525e59885