Paper Citation Record · LEDGER

MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2502.18439.

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

pith.paper-citation-record.v1
2502.18439 v2

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 2026-08-07T05:41:58.074609Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T22:56:37.761475Z

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 59f1180e-7ae6-4f72-bc1d-b3c437690746 · inbound

Chasing Moving Targets with Online Self-Play Reinforcement Learning for Safer Language Models cites this paper.

Chasing Moving Targets with Online Self-Play Reinforcement Learning for Safer Language Models MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:58.074609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 933c70b5-5273-4ec6-b898-39f5003ff99f · inbound

How to Train a Leader: Hierarchical Reasoning in Multi-Agent LLMs cites this paper.

How to Train a Leader: Hierarchical Reasoning in Multi-Agent LLMs MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T18:12:59.245532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09d02378-4a2f-4ca1-a9ea-74aa2e502278 · inbound

Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory cites this paper.

Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning

Reference 73

Resolution: verified exact; arxiv_id, observed 2026-05-14T23:13:16.345043Z

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 71c62a19-b786-4830-ae52-f314f7e889ac · inbound

Reinforced Collaboration in Multi-Agent Flow Networks cites this paper.

Reinforced Collaboration in Multi-Agent Flow Networks MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:42:57.164268Z

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 2afe8978-a761-4020-a386-deff09786e4b · inbound

Mathematical methods of reinforcement learning cites this paper.

Mathematical methods of reinforcement learning MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning

Reference 115

Resolution: verified exact; local_arxiv, observed 2026-07-09T22:56:37.762696Z

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 32bc3d0a-5ea1-4ec9-8350-fe11b4c5ec98 · inbound

Training with (Swap) Regret Loss in a Single-Layer Self-Attention Model: A Case Study on the Probability Simplex cites this paper.

Training with (Swap) Regret Loss in a Single-Layer Self-Attention Model: A Case Study on the Probability Simplex MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning

Reference 50

Resolution: unresolved; no resolver link, observed 2026-07-31T23:51:53.185192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.