Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MAGIC: Near-Optimal Data Attribution for Deep Learning
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2504.16430.
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 2026-08-11T00:35:48.407645Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T16:17:08.354831Z
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 4c7db193-a0bf-4e0e-85a7-89e3682e91f4 · inbound
Better Training Data Attribution via Better Inverse Hessian-Vector Products cites this paper.
Better Training Data Attribution via Better Inverse Hessian-Vector Products MAGIC: Near-Optimal Data Attribution for Deep Learning
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:54:42.424199Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 589b7f10-d0f3-4193-a0e8-645a5b32c470 · inbound
LLM generation novelty through the lens of semantic similarity cites this paper.
LLM generation novelty through the lens of semantic similarity MAGIC: Near-Optimal Data Attribution for Deep Learning
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T07:22:05.367970Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cf6fc1fa-11cb-4836-a304-ed9e132e9fde · inbound
Efficient Estimation of Kernel Surrogate Models for Task Attribution cites this paper.
Efficient Estimation of Kernel Surrogate Models for Task Attribution MAGIC: Near-Optimal Data Attribution for Deep Learning
Reference 5
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-16T08:00:44.858296Z
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.
Observation ece4c010-1723-45db-b8eb-2aad9ad3324b · inbound
How to sketch a learning algorithm cites this paper.
How to sketch a learning algorithm MAGIC: Near-Optimal Data Attribution for Deep Learning
Reference 10
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T05:30:56.453850Z
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.
Observation 11c75c0c-7f29-4b56-afba-2bdccf6d5149 · inbound
How Faithful Is Trajectory-Based Data Attribution? Error Sources, Remedies, and Practical Guidelines cites this paper.
How Faithful Is Trajectory-Based Data Attribution? Error Sources, Remedies, and Practical Guidelines MAGIC: Near-Optimal Data Attribution for Deep Learning
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T23:13:50.446204Z
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.
Observation 0877e611-a7e8-44be-a61b-f9f97bcfde6f · inbound
Position: Don't Just "Fix it in Post": A Science of AI Must Study Training Dynamics cites this paper.
Position: Don't Just "Fix it in Post": A Science of AI Must Study Training Dynamics MAGIC: Near-Optimal Data Attribution for Deep Learning
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T07:56:47.951304Z
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.
Observation 2ac5f64b-8551-47a0-9bdc-da75901720b0 · inbound
Small edits, large models: How Wikipedia advocacy shapes LLM values cites this paper.
Small edits, large models: How Wikipedia advocacy shapes LLM values MAGIC: Near-Optimal Data Attribution for Deep Learning
Reference 8
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-01T09:05:36.485562Z
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.
Observation 56ead02d-163d-4a52-9e1a-53f1a5415b7b · inbound
Small edits, large models: How Wikipedia advocacy shapes LLM values cites this paper.
Small edits, large models: How Wikipedia advocacy shapes LLM values MAGIC: Near-Optimal Data Attribution for Deep Learning
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T19:23:22.815333Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 24ec7b89-af0a-4242-aa7d-bde8c7fb848c · inbound
Prototype Language Models cites this paper.
Prototype Language Models MAGIC: Near-Optimal Data Attribution for Deep Learning
Reference 163
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-02T16:17:08.356434Z
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.
Observation a3d87da3-04e9-4c0d-a488-405dc6c7736c · inbound
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators cites this paper.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators MAGIC: Near-Optimal Data Attribution for Deep Learning
Reference 80
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T00:35:48.407645Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.