Paper Citation Record · LEDGER

NExtLong: Toward Effective Long-Context Training without Long Documents

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2501.12766.

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

pith.paper-citation-record.v1
2501.12766 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:40:09.996269Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T11:17:24.563972Z

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 48b4e371-f0c5-4084-92ef-69e093ce72b9 · inbound

From System 1 to System 2: A Survey of Reasoning Large Language Models cites this paper.

From System 1 to System 2: A Survey of Reasoning Large Language Models NExtLong: Toward Effective Long-Context Training without Long Documents

Reference 253

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:36:24.431950Z

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 b3a1a969-801d-4be4-91d7-b2e5e67ff30b · inbound

MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent cites this paper.

MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent NExtLong: Toward Effective Long-Context Training without Long Documents

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-15T11:17:24.567598Z

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 b5722cbe-bd39-4a3e-ae62-3e775887f637 · inbound

MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent cites this paper.

MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent NExtLong: Toward Effective Long-Context Training without Long Documents

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T20:40:09.996269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 136bcd82-410a-4977-9243-58df5a5f1f00 · inbound

Libra: Large Chinese-based Safeguard for AI Content cites this paper.

Libra: Large Chinese-based Safeguard for AI Content NExtLong: Toward Effective Long-Context Training without Long Documents

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T12:17:38.656970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae8b22b1-d0f9-41cb-8a37-1b0031b7fe89 · inbound

Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL cites this paper.

Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL NExtLong: Toward Effective Long-Context Training without Long Documents

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-02T14:50:10.939315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.