Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
In2Core: Leveraging Influence Functions for Coreset Selection in Instruction Finetuning of Large Language Models
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2408.03560.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T17:25:14.011205Z
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
0
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 4e0f084a-db15-47c6-99e1-db2b659414d4 · inbound
Class-Proportional Coreset Selection for Difficulty-Separable Data cites this paper.
Class-Proportional Coreset Selection for Difficulty-Separable Data In2Core: Leveraging Influence Functions for Coreset Selection in Instruction Finetuning of Large Language Models
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:25:14.011205Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 884dbffc-4da6-4e53-8ab2-46a8bb84bc88 · inbound
A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models cites this paper.
A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models In2Core: Leveraging Influence Functions for Coreset Selection in Instruction Finetuning of Large Language Models
Reference 123
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:42:30.149162Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0fec7506-5ab3-4265-bc69-b08dbdde8f2c · inbound
Quantum Annealing for Machine Learning: Applications in Feature Selection, Instance Selection, and Clustering cites this paper.
Quantum Annealing for Machine Learning: Applications in Feature Selection, Instance Selection, and Clustering In2Core: Leveraging Influence Functions for Coreset Selection in Instruction Finetuning of Large Language Models
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:47:08.848541Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3a91f959-ecc6-4914-a65b-1cb45ba3bbd8 · inbound
GRACE: A Dynamic Coreset Selection Framework for Large Language Model Optimization cites this paper.
GRACE: A Dynamic Coreset Selection Framework for Large Language Model Optimization In2Core: Leveraging Influence Functions for Coreset Selection in Instruction Finetuning of Large Language Models
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T20:30:49.064697Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.