Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Training Data Attribution via Approximate Unrolled Differentiation
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2405.12186.
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 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:08:46.903859Z
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
1
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 bd25474d-9c55-43d6-857d-3142b934ff2b · inbound
Capturing the Temporal Dependence of Training Data Influence cites this paper.
Capturing the Temporal Dependence of Training Data Influence Training Data Attribution via Approximate Unrolled Differentiation
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T17:02:33.676883Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 483c882a-f64f-4e7d-acae-91c590f45f6e · inbound
Efficient Multi-Agent System Training with Data Influence-Oriented Tree Search cites this paper.
Efficient Multi-Agent System Training with Data Influence-Oriented Tree Search Training Data Attribution via Approximate Unrolled Differentiation
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T04:07:30.437834Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 77e482bb-db5d-46d4-b11c-e29867d8c0a4 · inbound
MAGIC: Near-Optimal Data Attribution for Deep Learning cites this paper.
MAGIC: Near-Optimal Data Attribution for Deep Learning Training Data Attribution via Approximate Unrolled Differentiation
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:08:46.903859Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 80fc41d0-17ec-41ec-9748-d54835f4572c · inbound
Daunce: Data Attribution through Uncertainty Estimation cites this paper.
Daunce: Data Attribution through Uncertainty Estimation Training Data Attribution via Approximate Unrolled Differentiation
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:56:14.438057Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c1800acf-baf2-4dcb-9391-ed2922cc871b · inbound
Better Training Data Attribution via Better Inverse Hessian-Vector Products cites this paper.
Better Training Data Attribution via Better Inverse Hessian-Vector Products Training Data Attribution via Approximate Unrolled Differentiation
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:54:42.418110Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 801940c5-ffe8-44dd-a511-4229c3c8f6e9 · inbound
What Is The Performance Ceiling of My Classifier? Utilizing Category-Wise Influence Functions for Pareto Frontier Analysis cites this paper.
What Is The Performance Ceiling of My Classifier? Utilizing Category-Wise Influence Functions for Pareto Frontier Analysis Training Data Attribution via Approximate Unrolled Differentiation
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T11:38:25.550434Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 886f89e9-31ef-42c4-a247-ea2348707e6d · inbound
Variance Reduction for Expectations with Diffusion Teachers cites this paper.
Variance Reduction for Expectations with Diffusion Teachers Training Data Attribution via Approximate Unrolled Differentiation
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T04:53:57.944260Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 40846ee9-8ff3-4e2d-a160-2d81711675ff · inbound
Variance Reduction for Expectations with Diffusion Teachers cites this paper.
Variance Reduction for Expectations with Diffusion Teachers Training Data Attribution via Approximate Unrolled Differentiation
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T05:45:24.640090Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation ef3f4805-4227-4989-9803-2738cfe415b7 · inbound
Validity Threats for Foundation Model Research cites this paper.
Validity Threats for Foundation Model Research Training Data Attribution via Approximate Unrolled Differentiation
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T07:36:44.910724Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 5701b543-758b-44e4-843f-6cc7046ba452 · inbound
Quantifying the Agreement Between Data-Influence and Data-Similarity to Understand LLM Behavior cites this paper.
Quantifying the Agreement Between Data-Influence and Data-Similarity to Understand LLM Behavior Training Data Attribution via Approximate Unrolled Differentiation
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-06-26T08:49:14.959164Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.