Paper Citation Record · LEDGER

GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2103.00123.

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

pith.paper-citation-record.v1
2103.00123 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:52:49.697076Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T17:22:42.031415Z

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 b0d60cd4-46fd-45a8-a180-5172c1066f19 · inbound

EPiC: Towards Lossless Speedup for Reasoning Training through Edge-Preserving CoT Condensation cites this paper.

EPiC: Towards Lossless Speedup for Reasoning Training through Edge-Preserving CoT Condensation GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T10:52:49.697076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a518858-a07e-4d6f-b6c0-8a188b7794c5 · inbound

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording cites this paper.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T19:50:41.280850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15fe70e1-9b0a-42c3-b6a3-5c3bd9d7ee43 · inbound

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning cites this paper.

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T15:55:29.254637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b17e60a6-114a-441c-a66f-294273ba2b14 · inbound

Gradient-Discrepancy Acquisition for Pool-Based Active Learning cites this paper.

Gradient-Discrepancy Acquisition for Pool-Based Active Learning GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T06:15:37.326773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4f1b6644-186d-4566-8c15-8905bf1129c8 · inbound

Gradient-Discrepancy Acquisition for Pool-Based Active Learning cites this paper.

Gradient-Discrepancy Acquisition for Pool-Based Active Learning GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-19T17:22:42.033265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8f6daf97-d261-4711-9fc0-f670468deaad · 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 GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T02:51:18.014028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.