Paper Citation Record · LEDGER

Keyword Matters: Unveiling the Energy Sensitivity of On-Device LLM Prompting

As of 14 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2607.22568.

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

pith.paper-citation-record.v1
2607.22568 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T12:37:17.291925Z

measured 12 of 12 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 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

12 of 12 outbound references displayed

verified exact0
verified fuzzy0
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 48429db2-feac-49a7-a626-ad75f9877fc7 · outbound

This paper cites Efficient Memory Management for Large Language Model Serving with PagedAttention.

Keyword Matters: Unveiling the Energy Sensitivity of On-Device LLM Prompting Efficient Memory Management for Large Language Model Serving with PagedAttention

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T12:37:16.449904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a383f0f7-8c5a-46b9-a699-9d4fb217e1bf · outbound

This paper cites InProceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 2511–2522, Singapore.

Keyword Matters: Unveiling the Energy Sensitivity of On-Device LLM Prompting InProceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 2511–2522, Singapore

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T12:37:16.580769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebdd4da8-e202-44f9-a867-ed678b1f55a6 · outbound

This paper cites https: //ai.meta.com/research/publications/the-l lama-3-herd-of-models/.

Keyword Matters: Unveiling the Energy Sensitivity of On-Device LLM Prompting https: //ai.meta.com/research/publications/the-l lama-3-herd-of-models/

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T12:37:16.648197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4096334-4b22-4090-9078-46e289559268 · outbound

This paper cites https://github.com/mlc- ai/mlc- llm.

Keyword Matters: Unveiling the Energy Sensitivity of On-Device LLM Prompting https://github.com/mlc- ai/mlc- llm

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T12:37:16.687157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 956d658c-2e88-4ebf-bd9f-3ee2d8ee99a2 · outbound

This paper cites https://github.com /NVIDIA/TensorRT-LLM.

Keyword Matters: Unveiling the Energy Sensitivity of On-Device LLM Prompting https://github.com /NVIDIA/TensorRT-LLM

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T12:37:16.786832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d8993ea-a3fc-4965-a412-14f8b52c6580 · outbound

This paper cites https://github.com/tatsu-lab /stanford_alpaca.

Keyword Matters: Unveiling the Energy Sensitivity of On-Device LLM Prompting https://github.com/tatsu-lab /stanford_alpaca

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T12:37:16.911184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a5fbe97-0626-4325-88b0-98fbd653379e · outbound

This paper cites https://busine ss.yelp.com/data/resources/open-dataset/.

Keyword Matters: Unveiling the Energy Sensitivity of On-Device LLM Prompting https://busine ss.yelp.com/data/resources/open-dataset/

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T12:37:17.163584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 663dc144-b379-45bd-80b0-0467f7879f59 · outbound

This paper cites Large Language Models Are Human-Level Prompt Engineers.

Keyword Matters: Unveiling the Energy Sensitivity of On-Device LLM Prompting Large Language Models Are Human-Level Prompt Engineers

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T12:37:17.291925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 178af1ac-c2a3-42f9-96c5-b38c5b027e9a · outbound

This paper cites Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models.

Keyword Matters: Unveiling the Energy Sensitivity of On-Device LLM Prompting Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-02T12:37:16.293093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93af7e13-a114-4135-89cb-5923ae512070 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

Keyword Matters: Unveiling the Energy Sensitivity of On-Device LLM Prompting Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-02T12:37:17.042022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc77ecf9-1083-4ac9-aae9-c72572a57d35 · outbound

This paper cites Active Prompting with Chain-of-Thought for Large Language Models.

Keyword Matters: Unveiling the Energy Sensitivity of On-Device LLM Prompting Active Prompting with Chain-of-Thought for Large Language Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-02T12:37:16.379427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c38036c8-6617-4fa2-abb6-0c6715b6b375 · outbound

This paper cites MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases.

Keyword Matters: Unveiling the Energy Sensitivity of On-Device LLM Prompting MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-02T12:37:16.511857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.