Paper Citation Record · LEDGER

Designing Large Foundation Models for Efficient Training and Inference: A Survey

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2409.01990.

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

pith.paper-citation-record.v1
2409.01990 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:38:36.345090Z

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

5
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 1edceeba-caa0-4d5a-a285-9c7008dfc716 · inbound

Anomaly Detection and Early Warning Mechanism for Intelligent Monitoring Systems in Multi-Cloud Environments Based on LLM cites this paper.

Anomaly Detection and Early Warning Mechanism for Intelligent Monitoring Systems in Multi-Cloud Environments Based on LLM Designing Large Foundation Models for Efficient Training and Inference: A Survey

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T05:38:28.131425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f5e2dc9-0ad6-4294-89c4-f16c89f21be6 · inbound

An Intelligent Fault Self-Healing Mechanism for Cloud AI Systems via Integration of Large Language Models and Deep Reinforcement Learning cites this paper.

An Intelligent Fault Self-Healing Mechanism for Cloud AI Systems via Integration of Large Language Models and Deep Reinforcement Learning Designing Large Foundation Models for Efficient Training and Inference: A Survey

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T05:38:36.345090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e79d4ad8-ba53-4b01-bc0d-0daf919d372e · inbound

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead cites this paper.

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead Designing Large Foundation Models for Efficient Training and Inference: A Survey

Reference 214

Resolution: unresolved; no resolver link, observed 2026-08-06T21:36:38.395644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25f22337-0668-46b0-ac68-ce0c46574b32 · inbound

SemToken: Semantic-Aware Tokenization for Efficient Long-Context Language Modeling cites this paper.

SemToken: Semantic-Aware Tokenization for Efficient Long-Context Language Modeling Designing Large Foundation Models for Efficient Training and Inference: A Survey

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-05T18:07:39.465068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18f5aabe-e6a3-4ec4-98fe-390be31f5dde · inbound

CSV-Decode: Certifiable Sub-Vocabulary Decoding for Efficient Large Language Model Inference cites this paper.

CSV-Decode: Certifiable Sub-Vocabulary Decoding for Efficient Large Language Model Inference Designing Large Foundation Models for Efficient Training and Inference: A Survey

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T22:05:05.613847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8c26811-880f-4e6d-bd4c-dca52cbec786 · inbound

OLIVE: Online Low-Rank Incremental Learning for Efficient Adaptive Exoskeletons cites this paper.

OLIVE: Online Low-Rank Incremental Learning for Efficient Adaptive Exoskeletons Designing Large Foundation Models for Efficient Training and Inference: A Survey

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-02T07:46:45.740262Z

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 0102dc7f-2468-49d1-bb93-a4e763fd9a6d · inbound

OLIVE: Online Low-Rank Incremental Learning for Efficient Adaptive Exoskeletons cites this paper.

OLIVE: Online Low-Rank Incremental Learning for Efficient Adaptive Exoskeletons Designing Large Foundation Models for Efficient Training and Inference: A Survey

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T12:28:16.281090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a375771a-73b8-4202-83e7-f38bc85ff075 · inbound

Safe and Adaptive Cloud Healing: Verifying LLM-Generated Recovery Plans with a Neural-Symbolic World Model cites this paper.

Safe and Adaptive Cloud Healing: Verifying LLM-Generated Recovery Plans with a Neural-Symbolic World Model Designing Large Foundation Models for Efficient Training and Inference: A Survey

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:58:32.271269Z

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.