Paper Citation Record · LEDGER

Learning to Generate Structured Output with Schema Reinforcement Learning

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2502.18878.

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

pith.paper-citation-record.v1
2502.18878 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 2026-08-23T06:30:58.430688+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:59:32.723160Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

1
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 66ea87f6-3dcf-4014-892d-ea88004240ea · inbound

A Technical Survey of Reinforcement Learning Techniques for Large Language Models cites this paper.

A Technical Survey of Reinforcement Learning Techniques for Large Language Models Learning to Generate Structured Output with Schema Reinforcement Learning

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-06T19:59:32.723160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f14983ac-e856-4fe3-8acd-4932159c7eed · inbound

A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data cites this paper.

A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data Learning to Generate Structured Output with Schema Reinforcement Learning

Reference 140

Resolution: unresolved; no resolver link, observed 2026-08-03T08:15:24.731938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7852e5ee-89b0-40e9-8f72-b4afdb5c8030 · inbound

Omni-RRM: Advancing Omni Reward Modeling via Automatic Rubric-Grounded Preference Synthesis cites this paper.

Omni-RRM: Advancing Omni Reward Modeling via Automatic Rubric-Grounded Preference Synthesis Learning to Generate Structured Output with Schema Reinforcement Learning

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-03T06:00:46.754400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00b7f5a9-6064-4047-9496-0260a7745a35 · inbound

Ontology-constrained multi-LLM scoring of hypothesis support in the predictive processing literature cites this paper.

Ontology-constrained multi-LLM scoring of hypothesis support in the predictive processing literature Learning to Generate Structured Output with Schema Reinforcement Learning

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T11:54:37.871337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 182dc1ff-2fd6-4c4f-90e4-64ff9e8dcee4 · inbound

SelPE: Progressive Selection for Private Structured Text Synthesis cites this paper.

SelPE: Progressive Selection for Private Structured Text Synthesis Learning to Generate Structured Output with Schema Reinforcement Learning

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-07-04T10:49:46.965340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 50ba14ee-7892-41f1-b85d-07872512187b · inbound

ASMR: Agentic Schema Generation for Ship Maintenance Report Writing cites this paper.

ASMR: Agentic Schema Generation for Ship Maintenance Report Writing Learning to Generate Structured Output with Schema Reinforcement Learning

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-07-10T11:57:03.470459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.