Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Can Large Language Model Summarizers Adapt to Diverse Scientific Communication Goals?
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2401.10415.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T21:54:08.410226Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T11:52:35.935349Z
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 059852e2-f1fe-42cf-a3e1-34bdc274380c · inbound
Koel-TTS: Enhancing LLM based Speech Generation with Preference Alignment and Classifier Free Guidance cites this paper.
Koel-TTS: Enhancing LLM based Speech Generation with Preference Alignment and Classifier Free Guidance Can Large Language Model Summarizers Adapt to Diverse Scientific Communication Goals?
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T21:54:08.410226Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f150f263-88fe-4ab5-ae9b-7b3e8c1ae8ea · inbound
Beyond In-Context Learning: Aligning Long-form Generation of Large Language Models via Task-Inherent Attribute Guidelines cites this paper.
Beyond In-Context Learning: Aligning Long-form Generation of Large Language Models via Task-Inherent Attribute Guidelines Can Large Language Model Summarizers Adapt to Diverse Scientific Communication Goals?
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T11:52:35.939613Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.