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Paper Citation Record · LEDGER

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices

As of 11 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2501.07139.

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

pith.paper-citation-record.v1
2501.07139 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:56:20.810881Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-17T04:17:31.955480Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T04:19:00.475622Z

Reference resolution

34 of 34 outbound references displayed

  • verified exact0
  • verified fuzzy14
  • unresolved20
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

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Outbound references

Observation 37c7d6ff-34c7-49e7-b52c-5a0ebe6f3219 · outbound

This paper cites Introducing Copilot+ PCs - The Official Microsoft Blog,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Introducing Copilot+ PCs - The Official Microsoft Blog,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 6819c35e-51d7-4078-8c6d-bb6366598d07 · outbound

This paper cites Introducing Apple Foundation Mod- els,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Introducing Apple Foundation Mod- els,

Reference 2

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Observation 706bae7c-9709-49e7-9ea2-afe0f7b3b1d3 · outbound

This paper cites Google AI Edge — Google AI for Developers,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Google AI Edge — Google AI for Developers,

Reference 3

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source=pdf_text observed=2026-08-10T20:56:20.675820Z digest=sha256:9d46bf7959d89fb2ca8466bd95e212207b7154749264eeafe7f639cd87568d62

Observation 9c01d506-a603-4c5f-ac76-59ed09b31fda · outbound

This paper cites How to bring your AI Model to Android devices,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices How to bring your AI Model to Android devices,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:56:20.680381Z digest=sha256:084840e4d618bbed3b93a8774861d551d502d44adbb8cce6999fb852405d29af

Observation d638f7f6-3334-4ce2-84bb-6fe1e73cd18b · outbound

This paper cites Gemini Nano is now available on Android via ex- perimental access,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Gemini Nano is now available on Android via ex- perimental access,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:56:20.685448Z digest=sha256:2834fa7c0bd16e1a9c5b22828b1a84e8af3b44297ec21498747e1b2dec180ba1

Observation c3eaed91-ec71-4584-b267-20d7e1f5a06b · outbound

This paper cites Snapdragon X Elite Product Brief,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Snapdragon X Elite Product Brief,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:56:20.690520Z digest=sha256:6547db3a6d85b4fdfb486adeb4c185d5a8cb059cd3f5f84909d310a0c07bfac0

Observation 54156536-7bcb-4abe-87b6-e9b5165dc085 · outbound

This paper cites Retrieval- augmented generation for knowledge-intensive nlp tasks,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Retrieval- augmented generation for knowledge-intensive nlp tasks,

Reference 7

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source=pdf_text observed=2026-08-10T20:56:20.695514Z digest=sha256:496b906aae266b864281f34f75df2f19785b5a2ee1f39fbc5692e6545d1761bd

Observation e519b634-24c6-4c47-bacf-d9e753672af5 · outbound

This paper cites NVIDIA Jetson AGX Orin — nvidia.com,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices NVIDIA Jetson AGX Orin — nvidia.com,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:56:20.699709Z digest=sha256:7ef3ee0dec36baadd3c69b6bceac3561b423d6845e6022af2b55be404ccd4144

Observation 564176d6-8754-46b2-b4f5-d6326e91656b · outbound

This paper cites Demystifying Unified Memory on Jetson — GTC Digital Spring 2022 — NVIDIA On-Demand — nvidia.com,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Demystifying Unified Memory on Jetson — GTC Digital Spring 2022 — NVIDIA On-Demand — nvidia.com,

Reference 9

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source=pdf_text observed=2026-08-10T20:56:20.704048Z digest=sha256:e4d5e3bcd299fa50d82bfa75121b63942a22875cb235d3e22915254462305101

Observation 03543028-75fa-4e02-851c-8cc2b17ad8be · outbound

This paper cites Apple introduces M4 Pro and M4 Max,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Apple introduces M4 Pro and M4 Max,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 5be6e589-4917-4b06-bd1c-0b0b8230479d · outbound

This paper cites GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:56:20.712515Z digest=sha256:c1b64bc36efcb2c4fed7c21fb39489d7908fac32f4ab66f6a40e510a7bc7f983

Observation d811b942-77ca-475f-9856-68d966711580 · outbound

This paper cites Smoothquant: Accurate and efficient post-training quantization for large language models,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Smoothquant: Accurate and efficient post-training quantization for large language models,

Reference 12

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source=pdf_text observed=2026-08-10T20:56:20.717321Z digest=sha256:778960a194260fc9f5481d6631f472bed09b43e2ec6d61ef27be72cea136d643

Observation c36d3bce-e630-4e08-8f9b-165f0b5e7c4b · outbound

This paper cites Any-precision LLM: Low-cost deployment of multiple, different-sized LLMs,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Any-precision LLM: Low-cost deployment of multiple, different-sized LLMs,

Reference 13

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:56:20.722061Z digest=sha256:02f51ed800a038037ae58f71f7d9f92b4bfdbdc604625bfc18d52c003f17838e

Observation f88a258f-7f1d-4def-a702-682ea89bb388 · outbound

This paper cites LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Reference 14

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source=pdf_text observed=2026-08-10T20:56:20.726481Z digest=sha256:f8544109547f12c17de184a38c826e83abc8ef828ef50a9b0c7280aaa5e2b966

Observation ee5dfc40-8b24-4f58-8226-8670d2f1dafe · outbound

This paper cites A White Paper on Neural Network Quantization.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices A White Paper on Neural Network Quantization

Reference 15

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source=pdf_text observed=2026-08-10T20:56:20.731054Z digest=sha256:c32d60d4967cd955ec1594fa3dcc287f360a0557e4fe1431ce5a74acc2c5c09f

Observation 546c6e91-2378-4d7f-b935-d5c1767416df · outbound

This paper cites SqueezeLLM: Dense-and-Sparse Quantization.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices SqueezeLLM: Dense-and-Sparse Quantization

Reference 16

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source=pdf_text observed=2026-08-10T20:56:20.735632Z digest=sha256:2fbf2c34db0630d3d9b12331c55de01010a84ff3c4ddd4b19cab000a738989e6

Observation c4403bb3-9a9e-4421-aa1d-80a13f6c9856 · outbound

This paper cites Awq: Activation-aware weight quanti- zation for on-device llm compression and acceleration,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Awq: Activation-aware weight quanti- zation for on-device llm compression and acceleration,

Reference 17

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Observation c782a4b0-6513-479f-8bf3-09726e0b074c · outbound

This paper cites Zeroquant: Efficient and affordable post-training quantization for large- scale transformers,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Zeroquant: Efficient and affordable post-training quantization for large- scale transformers,

Reference 18

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source=pdf_text observed=2026-08-10T20:56:20.744438Z digest=sha256:8702dbeac355518aa2260b452893a65922fb0c489892a39f4259eee738449195

Observation d36ed694-b2e0-4676-89ce-ebe3d3c44740 · outbound

This paper cites SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression

Reference 19

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source=pdf_text observed=2026-08-10T20:56:20.748730Z digest=sha256:79b329846a9e725a971e5c4df883acdd05a0ee63e73a4b0386ad2556ab54e8d6

Observation d2eb4c64-5caf-4789-9677-c553051f6c73 · outbound

This paper cites Up or down? adaptive rounding for post-training quantization,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Up or down? adaptive rounding for post-training quantization,

Reference 20

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Observation 8a20c4e2-cf80-41e2-b488-1404a70921e6 · outbound

This paper cites Elms: Elasticized large language models on mobile devices,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Elms: Elasticized large language models on mobile devices,

Reference 21

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source=pdf_text observed=2026-08-10T20:56:20.757593Z digest=sha256:bed6f5bb4c0a24111535ce95fa66d7bfa8ad3516160eb16721fd981de7107f5f

Observation 69ea1b72-5b66-412d-9575-b3ec151a9caf · outbound

This paper cites LLM as a System Service on Mobile Devices.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices LLM as a System Service on Mobile Devices

Reference 22

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source=pdf_text observed=2026-08-10T20:56:20.761697Z digest=sha256:edad3f0350d5d13061e7103e1745e044402f45db179e7e13e3b665f85e66024d

Observation d82262ca-2113-4b92-b520-e53c334a65bd · outbound

This paper cites End the senseless killing: Improving memory management for mobile operating systems,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices End the senseless killing: Improving memory management for mobile operating systems,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:56:20.766677Z digest=sha256:5b5ddba94090646c4889acc234dad3a66559470dd6f94bc42410158c3d1ca32d

Observation 6079c2ac-6ae7-40d0-972b-98df799e7405 · outbound

This paper cites Efficient selectivity and backup operators in monte-carlo tree search,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Efficient selectivity and backup operators in monte-carlo tree search,

Reference 24

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Observation 81d46128-713b-41f6-b7ee-fdd022e0937d · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices LLaMA: Open and Efficient Foundation Language Models

Reference 25

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Observation 40e8b55d-1d2d-4df4-bdc5-64460b1e5f45 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 26

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source=pdf_text observed=2026-08-10T20:56:20.778966Z digest=sha256:6c34ec8f40774eee7381fa3cf03c4f2779e05568ef253b23216ebad60db4265f

Observation 60521ace-9a35-4617-9d24-ffd19a8346b9 · outbound

This paper cites The Llama 3 Herd of Models.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices The Llama 3 Herd of Models

Reference 27

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source=pdf_text observed=2026-08-10T20:56:20.782845Z digest=sha256:3b129d09c9ea7cf2cac0909ceaacb33f39a21e50cfbbe855900b72c970ed51e9

Observation 8d65c04b-fb71-4696-9841-c56820dd5250 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 28

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source=pdf_text observed=2026-08-10T20:56:20.786663Z digest=sha256:337f5e7f615b52bf378414450a8e6482e7f617f41015d04de4694de22c92dd89

Observation dbe3138e-03ad-4d87-abf6-750638a641c4 · outbound

This paper cites Pointer Sentinel Mixture Models.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Pointer Sentinel Mixture Models

Reference 29

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source=pdf_text observed=2026-08-10T20:56:20.790669Z digest=sha256:85a24b527975632c69184bdb380be02c263354fe0f3128ce1632322150c441ef

Observation 52b56e4f-9431-4edc-bddf-5a5ee2326879 · outbound

This paper cites Building a large annotated corpus of english: the penn treebank,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Building a large annotated corpus of english: the penn treebank,

Reference 30

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:56:20.794835Z digest=sha256:31564aaff8edf59441d9024d74c929b37a90ba572061e92ae3840bdbc26a9590

Observation 8394fd10-b35d-45d1-8d40-42cbdfa773d8 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 31

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source=pdf_text observed=2026-08-10T20:56:20.798690Z digest=sha256:c5144b5438416c2dcedff1e41b39fff9590c6884caf40fb22cabef81bba58bfd

Observation b16485a2-9063-4653-bb0b-6b946e1d778a · outbound

This paper cites HellaSwag: Can a Machine Really Finish Your Sentence?.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 32

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source=pdf_text observed=2026-08-10T20:56:20.802554Z digest=sha256:5237aacfde109fc2be43b7ee40ff0c81dd4a0a4dc2eacdcd3f80171c11a91ef5

Observation 11e9d0d3-492d-4fa6-90a9-29444339f2a9 · outbound

This paper cites Piqa: Reasoning about physical commonsense in natural language,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Piqa: Reasoning about physical commonsense in natural language,

Reference 33

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raw_fallback, observed 2026-08-10T20:56:21.117586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:56:20.806599Z digest=sha256:f54285e5e3169f6b2eb9a424980eb29cbe7f20ccb5b0e8fabca22ea8c6012ad9

Observation efcb28c3-a6cb-4b18-ae89-541cc8340ab6 · outbound

This paper cites Winogrande: An adversarial winograd schema challenge at scale,.

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices Winogrande: An adversarial winograd schema challenge at scale,

Reference 34

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source=pdf_text observed=2026-08-10T20:56:20.810881Z digest=sha256:6721031ceb48dc726a6a8025ad6dba71378dd381829c9506bd092f62eea1fa86

Pith citing papers

Observation 0838f317-4f68-4a38-ae21-73fa45d6e066 · inbound

DisCEdge: Distributed Context Management for Large Language Models at the Edge cites this paper.

DisCEdge: Distributed Context Management for Large Language Models at the Edge FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices

Reference 5

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arxiv_id, observed 2026-05-17T04:19:00.478298Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-17T04:17:31.955480Z digest=sha256:55064d357c18a46b1dc2b4403baa2166c4269139c4bdb5e941efc3a036ce05fe