Paper Citation Record · LEDGER

Generative AI on the Edge: Architecture and Performance Evaluation

As of 20 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2411.17712.

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

pith.paper-citation-record.v1
2411.17712 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:19:51.019383Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

16 of 16 outbound references displayed

verified exact0
verified fuzzy10
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 736768b3-9872-487d-b4b4-cc5f39471c2e · outbound

This paper cites 5g nr; technical specification group radio access network; nr; release 18, 2023.

Generative AI on the Edge: Architecture and Performance Evaluation 5g nr; technical specification group radio access network; nr; release 18, 2023

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:19:51.324849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 64f18834-3ee3-491a-bcc6-0ce751c2aee1 · outbound

This paper cites Imagenet classification with deep convolutional neural networks.

Generative AI on the Edge: Architecture and Performance Evaluation Imagenet classification with deep convolutional neural networks

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T18:19:50.938428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6471cd48-3390-45e6-8a73-f6702e25d587 · outbound

This paper cites Learning to for- get: Continual prediction with lstm.

Generative AI on the Edge: Architecture and Performance Evaluation Learning to for- get: Continual prediction with lstm

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:19:51.294604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4638e919-63c2-4f0d-ad39-84f2c75ec769 · outbound

This paper cites Attention is all you need.

Generative AI on the Edge: Architecture and Performance Evaluation Attention is all you need

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T18:19:50.950257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a438da52-656c-4ca8-a43a-23cab28744c1 · outbound

This paper cites MELTing point: Mobile Evaluation of Language Transformers.

Generative AI on the Edge: Architecture and Performance Evaluation MELTing point: Mobile Evaluation of Language Transformers

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T18:19:50.957530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0647bae0-04bf-4a64-abdb-b0a6fdce3952 · outbound

This paper cites an unresolved cited work.

Generative AI on the Edge: Architecture and Performance Evaluation Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-12T18:19:51.264769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ae318cb0-ba2f-4ebd-8877-09752b673863 · outbound

This paper cites Mobile-llama: Instruction fine-tuning open-source llm for network anal- ysis in 5g networks.

Generative AI on the Edge: Architecture and Performance Evaluation Mobile-llama: Instruction fine-tuning open-source llm for network anal- ysis in 5g networks

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:19:51.247091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 64348786-4f5e-449a-b965-c4c0de8cf55c · outbound

This paper cites Efficient memory management for large language model serving with pagedattention.

Generative AI on the Edge: Architecture and Performance Evaluation Efficient memory management for large language model serving with pagedattention

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T18:19:50.976248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7104f2ce-ae09-4d9d-9d47-7c321d01f8ac · outbound

This paper cites Ai benchmark: Running deep neural networks on android smartphones.

Generative AI on the Edge: Architecture and Performance Evaluation Ai benchmark: Running deep neural networks on android smartphones

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:19:51.217200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 144ebfb6-ac05-4cb5-93f2-f05dc22af9c3 · outbound

This paper cites Mlperf inference benchmark.

Generative AI on the Edge: Architecture and Performance Evaluation Mlperf inference benchmark

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:19:51.197676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 46559094-b2b9-4cd0-bfb7-df6162c61ab0 · outbound

This paper cites A first look at deep learning apps on smartphones.

Generative AI on the Edge: Architecture and Performance Evaluation A first look at deep learning apps on smartphones

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:19:51.179360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e5e5272b-b821-41aa-b626-ebdf7c22c31d · outbound

This paper cites A survey on mobile edge computing: The communication perspective.

Generative AI on the Edge: Architecture and Performance Evaluation A survey on mobile edge computing: The communication perspective

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:19:51.159914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d7ca1143-7bcc-4653-ae3d-c1020d53a7fd · outbound

This paper cites Zero: Memory optimizations toward training trillion parameter models.

Generative AI on the Edge: Architecture and Performance Evaluation Zero: Memory optimizations toward training trillion parameter models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T18:19:51.003190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c6e0fd3-c488-4f95-a0ca-0e1e12542cc7 · outbound

This paper cites Zeus: Understand- ing and optimizing GPU energy consumption of DNN training.

Generative AI on the Edge: Architecture and Performance Evaluation Zeus: Understand- ing and optimizing GPU energy consumption of DNN training

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:19:51.126820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8f1b24e3-d926-44c1-a108-f6313f4b45d4 · outbound

This paper cites Deepspeed-inference: enabling efficient inference of transformer models at unprecedented scale.

Generative AI on the Edge: Architecture and Performance Evaluation Deepspeed-inference: enabling efficient inference of transformer models at unprecedented scale

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:19:51.104591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d52caac2-d1a1-41ae-a0c3-be6ef48051c3 · outbound

This paper cites A framework for few-shot language model evalua- tion.

Generative AI on the Edge: Architecture and Performance Evaluation A framework for few-shot language model evalua- tion

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:19:51.083330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.