Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Coresets for Data-efficient Training of Machine Learning Models
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1906.01827.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:55:29.862346Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T04:02:30.487808Z
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 da6a5df2-38fc-4d4c-9498-99235737c321 · inbound
LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models cites this paper.
LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models Coresets for Data-efficient Training of Machine Learning Models
Reference 6
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-17T05:19:22.468240Z
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 638db8d6-a720-4e53-adfe-908c98c2b5d7 · inbound
DUET: Optimizing Training Data Mixtures via Feedback from Unseen Evaluation Tasks cites this paper.
DUET: Optimizing Training Data Mixtures via Feedback from Unseen Evaluation Tasks Coresets for Data-efficient Training of Machine Learning Models
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T04:02:30.491188Z
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 2a43063c-e289-43d5-b3be-4685848fdde9 · inbound
GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning cites this paper.
GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning Coresets for Data-efficient Training of Machine Learning Models
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:55:29.862346Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ca729656-4975-45c9-a641-1b4b96d5095d · 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 Coresets for Data-efficient Training of Machine Learning Models
Reference 59
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T05:30:57.954309Z
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 1d606220-98e7-4f0b-9e34-6515d674bb5a · inbound
ContextualJailbreak: Evolutionary Red-Teaming via Simulated Conversational Priming cites this paper.
ContextualJailbreak: Evolutionary Red-Teaming via Simulated Conversational Priming Coresets for Data-efficient Training of Machine Learning Models
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T05:55:32.339262Z
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 0a5d0405-beb9-41cb-b4d1-f5a917ca9427 · inbound
Let the Target Select for Itself: Data Selection via Target-Aligned Paths cites this paper.
Let the Target Select for Itself: Data Selection via Target-Aligned Paths Coresets for Data-efficient Training of Machine Learning Models
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T02:51:17.970250Z
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 a776e847-b527-4634-b3b3-c3288688b747 · inbound
Coresets Before Score Sets: Evaluation-Unsupervised Prompt Subset Selection for LLM Benchmarks cites this paper.
Coresets Before Score Sets: Evaluation-Unsupervised Prompt Subset Selection for LLM Benchmarks Coresets for Data-efficient Training of Machine Learning Models
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T16:38:50.302371Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.