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Paper Citation Record · LEDGER

InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2303.04947.

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

pith.paper-citation-record.v1
2303.04947 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 2026-08-21T06:32:19.484+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:26:16.373663Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T22:05:05.662609Z

Reference resolution

0 of 0 outbound references displayed

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  • 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 8421adad-a751-4c78-af0e-5b187f025f60 · inbound

Instance-dependent Early Stopping cites this paper.

Instance-dependent Early Stopping InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-08T12:26:16.373663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T12:26:16.373663Z digest=sha256:38b3ecfc7cf397bbf357b3d4436151a5d7251c3e91262da92ea3ef435d504820

Observation c76ea08c-374c-4588-99e3-c699b1e0358b · inbound

RL-Selector: Reinforcement Learning-Guided Data Selection via Redundancy Assessment cites this paper.

RL-Selector: Reinforcement Learning-Guided Data Selection via Redundancy Assessment InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T22:45:59.939052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:45:59.939052Z digest=sha256:64c5c8bbb54874c81619b62429612e11781b4305b650321cd544789015ef6ff7

Observation 4367702a-6c57-44c3-859e-41be010f687c · inbound

Multimodal-Guided Dynamic Dataset Pruning for Robust and Efficient Data-Centric Learning cites this paper.

Multimodal-Guided Dynamic Dataset Pruning for Robust and Efficient Data-Centric Learning InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T16:45:02.762139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:45:02.762139Z digest=sha256:6a65f0cec46d54bf3306a67099a73c7ae6ad0ae6b4d043268f5f3c646d76d0d4

Observation 655cd42e-e420-43ac-8fd0-072efa711d96 · inbound

Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning cites this paper.

Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T16:39:56.268656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:39:56.268656Z digest=sha256:22f38adb5c974030571d8bef4857fee414022d1a3fbf503ea44026875a0ed782

Observation 37b42bd2-25fa-4ca6-9056-326e579df41d · inbound

Data Agent: Learning to Select Data via End-to-End Dynamic Optimization cites this paper.

Data Agent: Learning to Select Data via End-to-End Dynamic Optimization InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-15T15:26:10.934061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-15T15:23:23.950152Z digest=sha256:8229f21e414d5012019ff6900f6212782cad1af50e48ed4d2c0a41a3129fd764

Observation 785ed716-352c-40bd-9124-9c65858132a0 · inbound

OPERA: Online Data Pruning for Efficient Retrieval Model Adaptation cites this paper.

OPERA: Online Data Pruning for Efficient Retrieval Model Adaptation InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-03T02:34:20.139275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T02:34:20.139275Z digest=sha256:8fefcb82a761b1469f26995b8cdd4387ef5f10ea90a41c951765933956f15585

Observation 0b317a89-29c5-45dc-b0eb-575420b862af · inbound

Beyond What to Select: A Plug-and-play Oscillatory Data-Volume Scheduling for Efficient Model Training cites this paper.

Beyond What to Select: A Plug-and-play Oscillatory Data-Volume Scheduling for Efficient Model Training InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-06-30T21:55:06.005804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-30T21:49:36.142405Z digest=sha256:985c3853d6539a7e717242c3628c2d04588f04be3c16a3941fce0e033ef20e2a

Observation 052248ca-7213-4798-b5d3-619601e1f77a · inbound

SLAP: Stratified Loss-based Pruning for On-Policy Data-Efficient Instruction Tuning cites this paper.

SLAP: Stratified Loss-based Pruning for On-Policy Data-Efficient Instruction Tuning InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-06-30T22:05:05.664193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-30T22:02:30.217607Z digest=sha256:8663dde06e9ad65f759051f0a50eb0025a3410cd30661c725c0dfdde6bcb9f3f

Observation 03e26409-0670-4bd3-ba20-6d1819113de9 · inbound

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training cites this paper.

Learning Faster without Deeper Networks: A*-Inspired Batch Selection for Efficient CNN Training InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-01T22:29:40.050893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:29:40.050893Z digest=sha256:6bd1f19a0c6cebb3e2d7564e361b94d1612c7fcaced96327e3fbdf4fefc2fc26