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Paper Citation Record · LEDGER

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators

As of 19 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2607.19438.

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

pith.paper-citation-record.v1
2607.19438 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T14:28:22.953274Z

measured 20 of 20 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 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

20 of 20 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved20
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 917cbc47-a43e-4734-a7d0-317a0af55f1d · outbound

This paper cites The next big shifts in AI workloads and hyperscaler strategies.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators The next big shifts in AI workloads and hyperscaler strategies

Reference 1

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no resolver link, observed 2026-08-01T14:28:21.328408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:21.328408Z digest=sha256:c35a938719e0dcf8b7251c419de89d227aa0cb477a4f547c1420ca4d5aefd635

Observation ec89ac0a-8a35-4a04-8860-def978c74569 · outbound

This paper cites Gartner predicts 40% of AI data breaches will arise from cross-border GenAI misuse by 2027.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators Gartner predicts 40% of AI data breaches will arise from cross-border GenAI misuse by 2027

Reference 2

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no resolver link, observed 2026-08-01T14:28:21.405227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:21.405227Z digest=sha256:a89af62f4229266be99bd865ca0b808df8f3c8eba36065d6064063a83a40f362

Observation b8d16cae-a90e-4947-9fd6-4550add7f33f · outbound

This paper cites Artificial intelligence risk management framework: Generative artificial intelligence profile.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators Artificial intelligence risk management framework: Generative artificial intelligence profile

Reference 3

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unresolved
no resolver link, observed 2026-08-01T14:28:21.465382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:21.465382Z digest=sha256:2da8201b919f710cd0f3394775090f731fa27fe1d2d7a6bcd1ebb4fc666f3e20

Observation 2bbbdf06-1b63-4ea9-9c99-bd34b524a8be · outbound

This paper cites DaDu-Corki: Algorithm-Architecture Co-Design for Embodied AI-powered Robotic Manipulation.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators DaDu-Corki: Algorithm-Architecture Co-Design for Embodied AI-powered Robotic Manipulation

Reference 4

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unresolved
no resolver link, observed 2026-08-01T14:28:21.557312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:21.557312Z digest=sha256:f8f33e0de2b3a977f5e27d9b3c026eef4c8a7365c1cbb4ee8e33b310a6c87c72

Observation 2e5f5688-65a4-48bc-94c3-454f67032f0e · outbound

This paper cites Agentic Artificial Intelligence: Architectures, Taxonomies, and Evaluation of Large Language Model Agents.arXiv preprint arXiv:2601.12560, 2026.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators Agentic Artificial Intelligence: Architectures, Taxonomies, and Evaluation of Large Language Model Agents.arXiv preprint arXiv:2601.12560, 2026

Reference 5

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unresolved
no resolver link, observed 2026-08-01T14:28:21.655863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:21.655863Z digest=sha256:77a50f0b6097f1ae9377bed8db50c10822635c655ecd134e0b4d916446e37a30

Observation afb5a434-8b04-48b2-bb97-fe96bb5fd551 · outbound

This paper cites Edge-First Language Model Inference: Models, Metrics, and Tradeoffs.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators Edge-First Language Model Inference: Models, Metrics, and Tradeoffs

Reference 6

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unresolved
no resolver link, observed 2026-08-01T14:28:21.783810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:21.783810Z digest=sha256:deecb624b5878b603697c7b4a1aac51c40e1cb54393ea96d87993e010d095dfa

Observation cdee5fd7-9da2-4f2f-bb42-f9a18323f73d · outbound

This paper cites Anthropic Status Page: Incident History.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators Anthropic Status Page: Incident History

Reference 7

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unresolved
no resolver link, observed 2026-08-01T14:28:21.840714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:21.840714Z digest=sha256:07e1b36036dddf90cb10d3a7d86c9e8ba06bae112e01fedbac8a272ae1b20e27

Observation 5d296c41-3ad4-4dbd-8630-d5b30fb75276 · outbound

This paper cites OpenAI Status Page: Incident History.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators OpenAI Status Page: Incident History

Reference 8

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unresolved
no resolver link, observed 2026-08-01T14:28:21.920879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:21.920879Z digest=sha256:739b87417494bf0bbf6ffa97de276d8aa326d0678ff90d16899576ba49b28fd1

Observation 47beab02-d644-4242-a39a-9bf05919c3bf · outbound

This paper cites The New Economics of Enterprise Technology in an AI World.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators The New Economics of Enterprise Technology in an AI World

Reference 9

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unresolved
no resolver link, observed 2026-08-01T14:28:21.983462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:21.983462Z digest=sha256:2d0234d0a5b78b3486a9f0d59eed6975f6a8c108f1e8eb164f0a9feb06d1eecd

Observation 1ee459cf-325f-4527-8bb4-8bedba2d21ea · outbound

This paper cites State of Open Source AI 2026.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators State of Open Source AI 2026

Reference 10

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no resolver link, observed 2026-08-01T14:28:22.039407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:22.039407Z digest=sha256:7de29f45189cf6361724ce5bcf2a7cb93887cb9246e38751833d6b9b275352e3

Observation 25a12513-3852-4837-af63-0ffead5d081e · outbound

This paper cites Profiling Large Language Model Inference on Apple Silicon: A Quantization Perspective.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators Profiling Large Language Model Inference on Apple Silicon: A Quantization Perspective

Reference 11

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unresolved
no resolver link, observed 2026-08-01T14:28:22.107077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:22.107077Z digest=sha256:b360ee16603b363e564e3fc8ef5bcd53af0bca508db9cf5079e27dc05d6906c2

Observation c21d9ed7-2c6f-433e-9ef1-34a968b56ec6 · outbound

This paper cites Artificial Intelligence Index Report 2025.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators Artificial Intelligence Index Report 2025

Reference 12

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unresolved
no resolver link, observed 2026-08-01T14:28:22.184070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:22.184070Z digest=sha256:4822d4ccda84fb728bc7e788924eacf2f967ca068fdbd51dd64f6e14da37a7fd

Observation cf982e02-09b5-45f7-b418-2ba08c2490af · outbound

This paper cites BaseRT: Best-in-Class LLM Inference on Apple Silicon via Native Metal.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators BaseRT: Best-in-Class LLM Inference on Apple Silicon via Native Metal

Reference 13

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unresolved
no resolver link, observed 2026-08-01T14:28:22.244763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:22.244763Z digest=sha256:63877b613b9e61c0762afcdd6b1b95345f074f6a8cdbc478b82dee3ec5ecac14

Observation 48685e4e-9170-4b00-9298-14e01d914fcf · outbound

This paper cites llama.cpp: LLM inference in C/C++.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators llama.cpp: LLM inference in C/C++

Reference 14

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unresolved
no resolver link, observed 2026-08-01T14:28:22.365220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:22.365220Z digest=sha256:f28216b857a43011750d78df54c2c1b53d35960b2e40ad7ad43ffd5730233e74

Observation 2db8dbf9-6245-46d7-9356-48a5135b5c48 · outbound

This paper cites MLX: Efficient and flexible machine learning on Apple silicon.https://github.com/ml-explore/mlx, 2023.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators MLX: Efficient and flexible machine learning on Apple silicon.https://github.com/ml-explore/mlx, 2023

Reference 15

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no resolver link, observed 2026-08-01T14:28:22.480763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:22.480763Z digest=sha256:5eff6c43e126ce2b6a1d687ddde049db7158d22bd689272821e32b2f205cfc6e

Observation 45623c91-08b9-4fcd-9826-7450d398986b · outbound

This paper cites Apple unleashes M5, the next big leap in AI performance for Apple silicon.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators Apple unleashes M5, the next big leap in AI performance for Apple silicon

Reference 16

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unresolved
no resolver link, observed 2026-08-01T14:28:22.588686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:22.588686Z digest=sha256:65f354938e709ecda240298fed0b8dbcc491eccad1a3dcf012f99d253ae80755

Observation 222a9cfa-2be7-4510-b16b-ceb7bac097b2 · outbound

This paper cites an unresolved cited work.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators Unresolved cited work

Reference 17

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unresolved
no resolver link, observed 2026-08-01T14:28:22.644790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:22.644790Z digest=sha256:de9d234ce28c86a5f040c42e4898f604df78ec10e441cd2a1920727e3b46d0e4

Observation 7eb07e12-ee72-4d06-831b-b4c48e1ab3ba · outbound

This paper cites Metal Performance Primitives (MPP) Programming Guide.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators Metal Performance Primitives (MPP) Programming Guide

Reference 18

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no resolver link, observed 2026-08-01T14:28:22.706340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:22.706340Z digest=sha256:bce8f5e770f3e91327f3e2cbc6f315685f27186d8d880164aaf6433405452f0c

Observation 01767eae-cea1-472b-9131-b58d8712e579 · outbound

This paper cites Discover Metal 4 tensors and Metal performance primitives.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators Discover Metal 4 tensors and Metal performance primitives

Reference 19

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unresolved
no resolver link, observed 2026-08-01T14:28:22.845966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:22.845966Z digest=sha256:d224056ed5cb527286280351a3fe845519c7a0e5adc49e513633777de4b0a893

Observation 7163ff69-6fc7-41ab-a61b-4a8ff7f07d77 · outbound

This paper cites Metal Shading Language Specification.

BaseRT: Advancing Best-in-Class LLM Inference with Apple M5 Neural Accelerators Metal Shading Language Specification

Reference 20

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unresolved
no resolver link, observed 2026-08-01T14:28:22.953274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:28:22.953274Z digest=sha256:502cf1d334cf7fdc3ad3a67e6e808409d86442032cc94bbfb3f46e511bbfdb59

Pith citing papers

No inbound Pith citation observations are available.