Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
tasksource: A Dataset Harmonization Framework for Streamlined NLP Multi-Task Learning and Evaluation
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2301.05948.
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 2026-08-07T15:26:09.883297Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, 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
3
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation eecb8ac0-e54e-4f56-b05b-9a4354ca9c14 · inbound
R-TOFU: Unlearning in Large Reasoning Models cites this paper.
R-TOFU: Unlearning in Large Reasoning Models tasksource: A Dataset Harmonization Framework for Streamlined NLP Multi-Task Learning and Evaluation
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:26:09.883297Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9a684d4c-e6a6-410d-9b40-27e0eed2c725 · inbound
FActBench: A Benchmark for Fine-grained Automatic Evaluation of LLM-Generated Text in the Medical Domain cites this paper.
FActBench: A Benchmark for Fine-grained Automatic Evaluation of LLM-Generated Text in the Medical Domain tasksource: A Dataset Harmonization Framework for Streamlined NLP Multi-Task Learning and Evaluation
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T11:49:36.922834Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2b1dcf90-aaa8-4d58-84ae-609676065e07 · inbound
Leak@$k$: Unlearning Does Not Make LLMs Forget Under Probabilistic Decoding cites this paper.
Leak@$k$: Unlearning Does Not Make LLMs Forget Under Probabilistic Decoding tasksource: A Dataset Harmonization Framework for Streamlined NLP Multi-Task Learning and Evaluation
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T23:39:09.021908Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4024e3bb-8105-4f44-8a36-1e5711ac9c57 · inbound
Response-free item difficulty modelling for multiple-choice items with fine-tuned transformers: Component-wise representation and multi-task learning cites this paper.
Response-free item difficulty modelling for multiple-choice items with fine-tuned transformers: Component-wise representation and multi-task learning tasksource: A Dataset Harmonization Framework for Streamlined NLP Multi-Task Learning and Evaluation
Reference 196
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T20:23:12.805955Z
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.