Paper Citation Record · LEDGER

Lumos: Efficient Performance Modeling and Estimation for Large-scale LLM Training

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2504.09307.

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

pith.paper-citation-record.v1
2504.09307 v1

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 2026-08-19T06:32:44.657259+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T22:28:47.034412Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T08:59:55.780761Z

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 e0f732da-6b9c-439c-b604-9f115791c3ea · inbound

Scalable Synthesis of distributed LLM workloads through Symbolic Tensor Graphs cites this paper.

Scalable Synthesis of distributed LLM workloads through Symbolic Tensor Graphs Lumos: Efficient Performance Modeling and Estimation for Large-scale LLM Training

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-03T22:28:47.034412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 610d2e36-d32b-472e-b9c5-780b84957fbd · inbound

MLCommons Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces cites this paper.

MLCommons Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces Lumos: Efficient Performance Modeling and Estimation for Large-scale LLM Training

Reference 75

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T01:47:05.076923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a2b53d43-360e-4a36-a0e4-447a5926a7d7 · inbound

MLCommons Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces cites this paper.

MLCommons Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces Lumos: Efficient Performance Modeling and Estimation for Large-scale LLM Training

Reference 75

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T22:19:07.594961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 130e176f-72fb-483c-a7f5-026bc8ff87c0 · inbound

Charon: A Unified and Fine-Grained Simulator for Large-Scale LLM Training and Inference cites this paper.

Charon: A Unified and Fine-Grained Simulator for Large-Scale LLM Training and Inference Lumos: Efficient Performance Modeling and Estimation for Large-scale LLM Training

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T14:13:21.206010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e02c2afd-4479-4925-8551-235e60720b78 · inbound

Charon: A Unified and Fine-Grained Simulator for Large-Scale LLM Training and Inference cites this paper.

Charon: A Unified and Fine-Grained Simulator for Large-Scale LLM Training and Inference Lumos: Efficient Performance Modeling and Estimation for Large-scale LLM Training

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-21T08:59:55.782545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bccfc25c-ef62-4f7b-8317-e62d3538d54a · inbound

TileSight: A First-Principles Tile-Centric Analytical GPU Performance Model from Cores to Clusters cites this paper.

TileSight: A First-Principles Tile-Centric Analytical GPU Performance Model from Cores to Clusters Lumos: Efficient Performance Modeling and Estimation for Large-scale LLM Training

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T04:49:47.386842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.