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Paper Citation Record · LEDGER

Language Grounded Multi-agent Reinforcement Learning with Human-interpretable Communication

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.17348.

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

pith.paper-citation-record.v1
2409.17348 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 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:11:34.223311Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T05:11:34.954295Z

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 0410a980-e9ca-41cb-abd7-7a2f0488ac13 · inbound

Wanting to Be Understood Explains the Meta-Problem of Consciousness cites this paper.

Wanting to Be Understood Explains the Meta-Problem of Consciousness Language Grounded Multi-agent Reinforcement Learning with Human-interpretable Communication

Reference 95

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:11:34.958458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-07T05:11:34.223311Z digest=sha256:e70aa0fa7989fab9afb73f74fc32f889875e690b3a07ce969062c2815db49b75

Observation 30b77d0a-6c86-48e7-b104-3d022d0dab7d · inbound

Prompting Robot Teams with Natural Language cites this paper.

Prompting Robot Teams with Natural Language Language Grounded Multi-agent Reinforcement Learning with Human-interpretable Communication

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-04T13:52:19.844742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T13:52:19.844742Z digest=sha256:65a324d4fb8414c2d153af6c2cba5504e05a710e9db11415e3fbca999ebd0f00