Paper Citation Record · LEDGER

Understanding Stragglers in Large Model Training Using What-if Analysis

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2505.05713.

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

pith.paper-citation-record.v1
2505.05713 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 2026-08-14T06:32:32.682623+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T07:56:28.490935Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T13:35:46.651338Z

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 916f10b7-2f63-4dc7-990e-6df830bcf5db · inbound

SLOTH: Lightweight Detection and Localization of On-Chip Fail-Slow Failures for DNN Accelerators cites this paper.

SLOTH: Lightweight Detection and Localization of On-Chip Fail-Slow Failures for DNN Accelerators Understanding Stragglers in Large Model Training Using What-if Analysis

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-04T07:56:28.490935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3ff529d-b3d9-46e5-8ea7-b8a05c71a8b9 · inbound

GhostServe: A Lightweight Checkpointing System in the Shadow for Fault-Tolerant LLM Serving cites this paper.

GhostServe: A Lightweight Checkpointing System in the Shadow for Fault-Tolerant LLM Serving Understanding Stragglers in Large Model Training Using What-if Analysis

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-15T00:38:23.118021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 99c29ada-e3e1-45c7-9822-86b8c96219fb · inbound

ResiHP: Taming LLM Training Failures with Dynamic Hybrid Parallelism cites this paper.

ResiHP: Taming LLM Training Failures with Dynamic Hybrid Parallelism Understanding Stragglers in Large Model Training Using What-if Analysis

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:31:15.923624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e8ac1c2b-a3a3-4685-999a-f0e076821a8b · inbound

ResiHP: Taming LLM Training Failures with Dynamic Hybrid Parallelism cites this paper.

ResiHP: Taming LLM Training Failures with Dynamic Hybrid Parallelism Understanding Stragglers in Large Model Training Using What-if Analysis

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:41:45.015153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0095ff5c-e1ac-4167-9e89-25afe6bd3b27 · inbound

From Detection to Recovery: Operational Analysis on LLM Pre-training with 504 GPUs cites this paper.

From Detection to Recovery: Operational Analysis on LLM Pre-training with 504 GPUs Understanding Stragglers in Large Model Training Using What-if Analysis

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-12T02:11:15.397558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c0cb717a-67db-4b86-b1a4-02ddd2a37be0 · inbound

From Detection to Recovery: Operational Analysis on LLM Pre-training with 504 GPUs cites this paper.

From Detection to Recovery: Operational Analysis on LLM Pre-training with 504 GPUs Understanding Stragglers in Large Model Training Using What-if Analysis

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:35:46.652992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.