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Paper Citation Record · LEDGER

Estimating Training Data Influence by Tracing Gradient Descent

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2002.08484.

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

pith.paper-citation-record.v1
2002.08484 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:45:03.064160Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T06:19:38.875861Z

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 7650d613-c445-4905-aa1f-af0ea6e173af · 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 Estimating Training Data Influence by Tracing Gradient Descent

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-23T04:02:30.439479Z

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.

source=pdf_text observed=2026-05-23T03:58:48.967122Z digest=sha256:db0177d006dbf6e9ad10ed99740df57c302e585eeb72e4d3a5cb34d0fe86ae33

Observation f2b3444f-c61d-4c34-a592-b81a78ae8b1a · inbound

Data Pruning by Information Maximization cites this paper.

Data Pruning by Information Maximization Estimating Training Data Influence by Tracing Gradient Descent

Reference 2015

Resolution
unresolved
no resolver link, observed 2026-08-07T11:45:03.064160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:45:03.064160Z digest=sha256:153b649c130cd826f59f8aef4f0e1b8542ad70bcef59fd1d5287ea2946e721c1

Observation da82ed8f-6d10-4dec-8218-dad46b4c3501 · inbound

Understanding Data Influence with Differential Approximation cites this paper.

Understanding Data Influence with Differential Approximation Estimating Training Data Influence by Tracing Gradient Descent

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-05T18:28:50.420152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:28:50.420152Z digest=sha256:913245eecaca0fde67f76928ec5971483279590b96bea9ba9b66e5ceb830005f

Observation 446f04a7-9d6d-434d-93ff-edcac189c2ed · inbound

When unlearning is free: leveraging low influence points to reduce computational costs cites this paper.

When unlearning is free: leveraging low influence points to reduce computational costs Estimating Training Data Influence by Tracing Gradient Descent

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-03T18:28:32.507165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T18:28:32.507165Z digest=sha256:16872cc35bffc4d4b258f7db42dce507884bff85345aeebec9a951f0cfd05a71

Observation 67c159ce-1e0d-43bb-9a02-e9d026560db4 · inbound

GUDA: Counterfactual Group-wise Training Data Attribution for Diffusion Models via Unlearning cites this paper.

GUDA: Counterfactual Group-wise Training Data Attribution for Diffusion Models via Unlearning Estimating Training Data Influence by Tracing Gradient Descent

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-03T06:35:43.109362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:35:43.109362Z digest=sha256:6fcb13cbe52b4ae2ba25634871e9357b955903a88bd1610c926ac05a0305b627

Observation f635a768-3758-424c-a018-f1e72d98b768 · inbound

Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation cites this paper.

Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation Estimating Training Data Influence by Tracing Gradient Descent

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-10T08:48:01.020637Z

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.

source=pdf_text observed=2026-05-10T08:47:36.122054Z digest=sha256:f7dbc74bdbc9fe91b29293559054cee7143da0a90dd871d9511b7f3cab0e017f

Observation 3352af87-c686-4285-9da9-d981d2c28f60 · inbound

Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation cites this paper.

Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation Estimating Training Data Influence by Tracing Gradient Descent

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-02T16:12:11.881072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T16:12:11.881072Z digest=sha256:8b9e1eef6b942faef2d49fb332bca325ab24feb5775c4b735573bfb0fddc09eb

Observation 7b219f61-860f-454c-9ac9-fd13d30be752 · 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 Estimating Training Data Influence by Tracing Gradient Descent

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-12T02:51:18.005919Z

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.

source=pdf_text observed=2026-05-12T02:47:55.649231Z digest=sha256:9159b7920153dfd055d426f3539ddd7afbdf0e2309da16765cc799b8d54e2088

Observation 8800ab39-58a8-4af0-87ae-710e28aadeee · inbound

SALT: When More Rollouts Don't Help in Group-Based Policy Optimization and How to Make Them Matter cites this paper.

SALT: When More Rollouts Don't Help in Group-Based Policy Optimization and How to Make Them Matter Estimating Training Data Influence by Tracing Gradient Descent

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-07-02T11:46:56.166054Z

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.

source=pdf_text observed=2026-06-28T02:53:22.159132Z digest=sha256:34789a96984841cf1ab85aa4dffc3548793ad84c58d29ba86b424553fdb0c926

Observation bf36f196-3744-4671-a195-093c825fdbd9 · inbound

Towards Dys-XAI: Influence-Based Explanations for Dysarthria Severity Assessment cites this paper.

Towards Dys-XAI: Influence-Based Explanations for Dysarthria Severity Assessment Estimating Training Data Influence by Tracing Gradient Descent

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-07-04T06:19:38.877819Z

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.

source=pdf_text observed=2026-06-26T14:31:46.594002Z digest=sha256:2c605b529f0031b56c1155e43fa3d967401457a8bb945be44389d05be02b3a64

Observation 80ed8efe-3b24-45f2-807e-4eba225cedd1 · inbound

Dataset Distillation by Influence Matching cites this paper.

Dataset Distillation by Influence Matching Estimating Training Data Influence by Tracing Gradient Descent

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-01T19:49:25.386620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T19:49:25.386620Z digest=sha256:8e3bb20b59f431b8227415273dc608733b9519df4e9324efc9c29eac1844c499