Paper Citation Record · LEDGER

Fast On-device LLM Inference with NPUs

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2407.05858.

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

pith.paper-citation-record.v1
2407.05858 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 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:40:18.640410Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T08:55:34.919133Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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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 e261bd07-9abd-4529-af59-f6e8c5324fb5 · inbound

Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction cites this paper.

Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction Fast On-device LLM Inference with NPUs

Reference 269

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:15:47.326325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c26d154b-e991-4125-bb3b-c7405ab12d61 · inbound

Fast and Cost-effective Speculative Edge-Cloud Decoding with Early Exits cites this paper.

Fast and Cost-effective Speculative Edge-Cloud Decoding with Early Exits Fast On-device LLM Inference with NPUs

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:18.640410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe35808c-870d-4fb1-a785-b9dfe18468cf · inbound

Dissecting the Impact of Mobile DVFS Governors on LLM Inference Performance and Energy Efficiency cites this paper.

Dissecting the Impact of Mobile DVFS Governors on LLM Inference Performance and Energy Efficiency Fast On-device LLM Inference with NPUs

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T20:44:17.677943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a78480c-e864-413e-b8bf-b0e5b0bb2613 · inbound

Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R cites this paper.

Efficient Deployment of Vision-Language Models on Mobile Devices: A Case Study on OnePlus 13R Fast On-device LLM Inference with NPUs

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T18:20:53.553489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a78eaf6-fd27-460a-ad2e-2b18d69aa4e5 · inbound

Less is More: Lightweight Prompt Compression for Question Answering Applications on Edge Devices cites this paper.

Less is More: Lightweight Prompt Compression for Question Answering Applications on Edge Devices Fast On-device LLM Inference with NPUs

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-07-01T08:55:34.920490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0f72777d-6744-43b2-a6c0-49aebcecae11 · inbound

Is Your NPU Ready for LLMs? Dissecting the Hidden Efficiency Bottlenecks in Mobile LLM Inference cites this paper.

Is Your NPU Ready for LLMs? Dissecting the Hidden Efficiency Bottlenecks in Mobile LLM Inference Fast On-device LLM Inference with NPUs

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-11T12:14:57.342551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.