Paper Citation Record · LEDGER

Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2507.21892.

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

pith.paper-citation-record.v1
2507.21892 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T16:07:36.099856Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T03:47:15.063741Z

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 d27170b6-546e-4b65-9cc0-d57f041da39b · inbound

Reinforcement Learning Meets Large Language Models: A Survey of Advancements and Applications Across the LLM Lifecycle cites this paper.

Reinforcement Learning Meets Large Language Models: A Survey of Advancements and Applications Across the LLM Lifecycle Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

Reference 117

Resolution: unresolved; no resolver link, observed 2026-08-04T16:07:36.099856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3aa3d38-dd30-4d51-bd6c-a22840562d38 · inbound

TeaRAG: A Token-Efficient Agentic Retrieval-Augmented Generation Framework cites this paper.

TeaRAG: A Token-Efficient Agentic Retrieval-Augmented Generation Framework Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-03T23:33:46.909528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 459052e6-0256-46be-bc96-30f62a209d92 · inbound

GraphScout: Empowering Large Language Models with Intrinsic Exploration Ability for Agentic Graph Reasoning cites this paper.

GraphScout: Empowering Large Language Models with Intrinsic Exploration Ability for Agentic Graph Reasoning Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-06-04T02:06:52.238547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d36cfe31-d688-4fd3-9621-cede8b50e75f · inbound

Do We Still Need GraphRAG? Benchmarking RAG and GraphRAG for Agentic Search Systems cites this paper.

Do We Still Need GraphRAG? Benchmarking RAG and GraphRAG for Agentic Search Systems Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-06-04T02:06:52.238547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e6114fc0-83e3-49f1-a209-83807b0edcde · inbound

MemSearch-o1: Empowering Large Language Models with Reasoning-Aligned Memory Growth in Agentic Search cites this paper.

MemSearch-o1: Empowering Large Language Models with Reasoning-Aligned Memory Growth in Agentic Search Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-06-04T02:06:52.238547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation eac70b6d-549a-4203-8a00-e423cf3de8ec · inbound

ONOTE: Benchmarking Omnimodal Notation Processing for Expert-level Music Intelligence cites this paper.

ONOTE: Benchmarking Omnimodal Notation Processing for Expert-level Music Intelligence Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-06-04T02:06:52.238547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6e807a61-4b79-486e-bf10-b44a7d57d27a · inbound

AtomicRAG: Atom-Entity Graphs for Retrieval-Augmented Generation cites this paper.

AtomicRAG: Atom-Entity Graphs for Retrieval-Augmented Generation Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-06-04T02:06:52.238547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 09f130b6-8182-4d7f-a0f8-583bb253d92a · inbound

DeepRefine: Agent-Compiled Knowledge Refinement via Reinforcement Learning cites this paper.

DeepRefine: Agent-Compiled Knowledge Refinement via Reinforcement Learning Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-06-04T02:06:52.238547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5ce34b70-f9c0-4cf0-8267-3784f20ecefe · inbound

Search-on-Graph-R1: Training Large Language Models to Search Knowledge Graphs with Reinforcement Learning cites this paper.

Search-on-Graph-R1: Training Large Language Models to Search Knowledge Graphs with Reinforcement Learning Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T15:21:29.455631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.