Paper Citation Record · LEDGER

Influence Functions in Deep Learning Are Fragile

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2006.14651.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2006.14651 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:02:33.692418Z

measured 1 of 1 external citation measurements

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

15
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 8caf1753-fd78-4fcb-90df-a803603abb16 · inbound

Capturing the Temporal Dependence of Training Data Influence cites this paper.

Capturing the Temporal Dependence of Training Data Influence Influence Functions in Deep Learning Are Fragile

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T17:02:33.692418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cd827d9-dd82-44ba-a4f7-8dd4a67dafd2 · inbound

Laplace Sample Information: Data Informativeness Through a Bayesian Lens cites this paper.

Laplace Sample Information: Data Informativeness Through a Bayesian Lens Influence Functions in Deep Learning Are Fragile

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T15:26:03.311096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f6c931e-69aa-46d8-8f61-5c8b3df774f2 · inbound

Newfluence: Boosting Model interpretability and Understanding in High Dimensions cites this paper.

Newfluence: Boosting Model interpretability and Understanding in High Dimensions Influence Functions in Deep Learning Are Fragile

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T17:05:25.232575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 155ca38e-bf19-4a8b-8f59-fb0c86678562 · inbound

Better Training Data Attribution via Better Inverse Hessian-Vector Products cites this paper.

Better Training Data Attribution via Better Inverse Hessian-Vector Products Influence Functions in Deep Learning Are Fragile

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T15:54:42.462806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c5a265b-d073-48e7-84cc-623214dc2f5f · inbound

Representation Unlearning: Forgetting through Information Compression cites this paper.

Representation Unlearning: Forgetting through Information Compression Influence Functions in Deep Learning Are Fragile

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-03T06:59:17.946918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d8bd7cf-efd1-4c18-a329-168b3b0ab529 · inbound

Erase Persona, Forget Lore: Benchmarking Multimodal Copyright Unlearning in Large Vision Language Models cites this paper.

Erase Persona, Forget Lore: Benchmarking Multimodal Copyright Unlearning in Large Vision Language Models Influence Functions in Deep Learning Are Fragile

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:11:17.939154Z

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 fc801fe8-9fd6-444f-868e-5798ffadf950 · inbound

Dynamic Shapley Computation cites this paper.

Dynamic Shapley Computation Influence Functions in Deep Learning Are Fragile

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-21T06:39:43.786677Z

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 71ea2a9d-af63-4bf7-8071-64b4024251bc · 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 Influence Functions in Deep Learning Are Fragile

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-06-26T08:49:14.932724Z

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 b1b46ba1-9d98-49d6-8793-21954dcaf65f · inbound

Influence Diagnostics in High-dimensional M-estimation: Precise Asymptotics cites this paper.

Influence Diagnostics in High-dimensional M-estimation: Precise Asymptotics Influence Functions in Deep Learning Are Fragile

Reference 120

Resolution: unresolved; no resolver link, observed 2026-07-13T04:24:43.867063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.