Paper Citation Record · LEDGER

Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2303.08114.

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

pith.paper-citation-record.v1
2303.08114 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T16:20:38.223631Z

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

7
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 49da94a5-ba5d-4592-9fc8-99793e945086 · inbound

PiKE: Adaptive Data Mixing for Large-Scale Multi-Task Learning Under Low Gradient Conflicts cites this paper.

PiKE: Adaptive Data Mixing for Large-Scale Multi-Task Learning Under Low Gradient Conflicts Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-08T16:20:38.223631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97adf9dc-8b66-410b-abf6-5114cd7a7516 · inbound

ClusterUCB: Efficient Gradient-Based Data Selection for Targeted Fine-Tuning of LLMs cites this paper.

ClusterUCB: Efficient Gradient-Based Data Selection for Targeted Fine-Tuning of LLMs Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T04:37:07.062387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44509aa4-dcbb-4ac5-a059-e3ed9a20661c · inbound

TuCo: Measuring the Contribution of Fine-Tuning to Individual Responses of LLMs cites this paper.

TuCo: Measuring the Contribution of Fine-Tuning to Individual Responses of LLMs Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T21:50:10.482727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 539279d3-aa13-4cc1-ba59-4bc9d5537bae · inbound

Low-Perplexity LLM-Generated Sequences and Where To Find Them cites this paper.

Low-Perplexity LLM-Generated Sequences and Where To Find Them Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T20:44:59.195398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2856289d-7b7d-471a-8bc5-a2a375b0c339 · inbound

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

Newfluence: Boosting Model interpretability and Understanding in High Dimensions Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T17:05:25.564344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0340cbe2-c608-40ce-96a7-7bef73112847 · inbound

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

Better Training Data Attribution via Better Inverse Hessian-Vector Products Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-06T15:54:42.653576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02b111b0-4ed9-4fe1-93be-80aabdf44f66 · inbound

Tracing the Roots: A Multi-Agent Framework for Uncovering Data Lineage in Post-Training LLMs cites this paper.

Tracing the Roots: A Multi-Agent Framework for Uncovering Data Lineage in Post-Training LLMs Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:06:00.550144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c97b76f7-7f36-4448-be14-cd07816c72ed · inbound

Correcting Influence: Unboxing LLM Outputs with Orthogonal Latent Spaces cites this paper.

Correcting Influence: Unboxing LLM Outputs with Orthogonal Latent Spaces Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs

Reference 199

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:17:55.573713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a5822f63-061c-4822-8fb7-cbfe2d8f1325 · 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 Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-20T23:13:50.477814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fd199f2c-c936-492e-955b-e196e53e8a65 · 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 Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs

Reference 96

Resolution: verified exact; arxiv_id, observed 2026-06-26T08:49:14.984720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.