Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Large Language Models Meet Harry Potter: A Bilingual Dataset for Aligning Dialogue Agents with Characters
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2211.06869.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:02:26.881130Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T09:21:02.394178Z
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 de71f6c6-1874-44a7-8913-4a7fa5d75eda · inbound
CogDual: Enhancing Dual Cognition of LLMs via Reinforcement Learning with Implicit Rule-Based Rewards cites this paper.
CogDual: Enhancing Dual Cognition of LLMs via Reinforcement Learning with Implicit Rule-Based Rewards Large Language Models Meet Harry Potter: A Bilingual Dataset for Aligning Dialogue Agents with Characters
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:02:26.881130Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3f10fe3f-e8ec-4994-8a6e-c5b240ef22c8 · inbound
ActorMind: Emulating Human Actor Reasoning for Speech Role-Playing cites this paper.
ActorMind: Emulating Human Actor Reasoning for Speech Role-Playing Large Language Models Meet Harry Potter: A Bilingual Dataset for Aligning Dialogue Agents with Characters
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T09:21:02.396789Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.