Paper Citation Record · LEDGER

MARFT: Multi-Agent Reinforcement Fine-Tuning

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2504.16129.

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

pith.paper-citation-record.v1
2504.16129 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T07:56:46.663818Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-04T13:49:51.542821Z

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 36f56b3d-8acd-4ef2-91d1-c7668399995e · inbound

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems cites this paper.

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems MARFT: Multi-Agent Reinforcement Fine-Tuning

Reference 168

Resolution: verified exact; arxiv_id, observed 2026-06-02T02:03:31.668542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f15f0f2e-b42b-43d9-8268-dc97d30a64e2 · inbound

A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems cites this paper.

A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems MARFT: Multi-Agent Reinforcement Fine-Tuning

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-06-02T02:03:31.668542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a4c744a8-7fc4-4fc7-a50f-d1ac819ee512 · inbound

MASPRM: Multi-Agent System Process Reward Model cites this paper.

MASPRM: Multi-Agent System Process Reward Model MARFT: Multi-Agent Reinforcement Fine-Tuning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T07:56:46.663818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b74506c-3120-45dc-b88d-5ae8aa0f055b · inbound

Memory in the Age of AI Agents cites this paper.

Memory in the Age of AI Agents MARFT: Multi-Agent Reinforcement Fine-Tuning

Reference 67

Resolution: metadata mismatch; arxiv_id, observed 2026-06-02T02:03:31.668542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3c7a5d6a-ba58-4d98-b73b-599239c6c62f · inbound

Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic cites this paper.

Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic MARFT: Multi-Agent Reinforcement Fine-Tuning

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-06-02T02:03:31.668542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f9d5ae1a-8d7a-4685-a6ea-d898d0abbce9 · inbound

Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic cites this paper.

Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic MARFT: Multi-Agent Reinforcement Fine-Tuning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T06:46:39.487517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d52a709f-a445-4e56-8c54-613947da1d0a · inbound

Learning from Self-Debate: Preparing Reasoning Models for Multi-Agent Debate cites this paper.

Learning from Self-Debate: Preparing Reasoning Models for Multi-Agent Debate MARFT: Multi-Agent Reinforcement Fine-Tuning

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-06-02T02:03:31.668542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d4118c98-6069-45c6-8a3f-0565b18f7ca4 · inbound

Joint Optimization of Multi-agent Memory System cites this paper.

Joint Optimization of Multi-agent Memory System MARFT: Multi-Agent Reinforcement Fine-Tuning

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-06-02T02:03:31.668542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 38277402-9449-402c-98e9-4dd9706248c1 · inbound

Reinforcement Learning for LLM-based Multi-Agent Systems through Orchestration Traces cites this paper.

Reinforcement Learning for LLM-based Multi-Agent Systems through Orchestration Traces MARFT: Multi-Agent Reinforcement Fine-Tuning

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-06-02T02:03:31.668542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5290e0a4-4aef-4a39-967a-aba1123935de · inbound

Tree-based Credit Assignment for Multi-Agent Memory System cites this paper.

Tree-based Credit Assignment for Multi-Agent Memory System MARFT: Multi-Agent Reinforcement Fine-Tuning

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-06-02T02:03:31.668542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d95171eb-2196-449b-a94b-089862af93c0 · inbound

AIPO: Learning to Reason from Active Interaction cites this paper.

AIPO: Learning to Reason from Active Interaction MARFT: Multi-Agent Reinforcement Fine-Tuning

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-06-02T02:03:31.668542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3a1659cf-20a2-4c84-ab5b-74896ef270df · inbound

AIPO: Learning to Reason from Active Interaction cites this paper.

AIPO: Learning to Reason from Active Interaction MARFT: Multi-Agent Reinforcement Fine-Tuning

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-06-02T02:03:31.668542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5913973e-4df3-422b-9779-3c5c0fabb6be · inbound

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

Reinforced Collaboration in Multi-Agent Flow Networks MARFT: Multi-Agent Reinforcement Fine-Tuning

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-06-02T02:03:31.668542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3f0151e0-bd36-4962-acfb-4667cca22f31 · inbound

Position: Agentic AI System Is a Foreseeable Pathway to AGI cites this paper.

Position: Agentic AI System Is a Foreseeable Pathway to AGI MARFT: Multi-Agent Reinforcement Fine-Tuning

Reference 41

Resolution: metadata mismatch; arxiv_id, observed 2026-06-02T02:03:31.668542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f771318b-14e8-45eb-841f-7b4481dbacac · inbound

Traj-Evolve: A Self-Evolving Multi-Agent System for Patient Trajectory Modeling in Lung Cancer Early Detection cites this paper.

Traj-Evolve: A Self-Evolving Multi-Agent System for Patient Trajectory Modeling in Lung Cancer Early Detection MARFT: Multi-Agent Reinforcement Fine-Tuning

Reference 48

Resolution: metadata mismatch; local_arxiv, observed 2026-07-01T23:26:22.822170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 112dcb44-05b2-4c69-8901-48c21d5a6403 · inbound

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning cites this paper.

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning MARFT: Multi-Agent Reinforcement Fine-Tuning

Reference 113

Resolution: verified exact; local_arxiv, observed 2026-07-04T08:09:40.650675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fec67690-d95e-4a18-9243-724f69b41a88 · inbound

Where Do CoT Training Gains Land in LLM based Agents? cites this paper.

Where Do CoT Training Gains Land in LLM based Agents? MARFT: Multi-Agent Reinforcement Fine-Tuning

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-07-04T13:49:51.544355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.