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Paper Citation Record · LEDGER

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models

As of 23 August 2026, this Paper Citation Record lists 100 of 155 outbound references and 0 inbound Pith citation observations for arXiv:2607.23047.

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

pith.paper-citation-record.v1
2607.23047 v1

Coverage vector

measured 100 of 155 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T03:51:32.664993Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

100 of 155 outbound references displayed

  • verified exact16
  • verified fuzzy0
  • unresolved81
  • parse uncertain2
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 25bf177a-2bd3-4505-b5bc-4b285cd22f05 · outbound

This paper cites Wood , title =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Wood , title =

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.375165Z digest=sha256:b30e5877a07dccb0fa44590bc0139247f3149bcd5399535427340b7a1160b9ec

Observation a9378ced-72d9-4d82-93fc-1832664a1ffd · outbound

This paper cites 2023 , url =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models 2023 , url =

Reference 2

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source=arxiv_source observed=2026-08-01T03:51:32.378836Z digest=sha256:8452fa7c4849feb84a63cdae83ed425269a9c51d3e496723bc961fdb3a936d8a

Observation 9817cb05-d58d-44f9-b8e6-f4b51d9265d4 · outbound

This paper cites Approximate Computing: A Survey , year=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Approximate Computing: A Survey , year=

Reference 3

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source=arxiv_source observed=2026-08-01T03:51:32.382620Z digest=sha256:2f3fad50906442ccba7d487d0eb2bc1871c4dd12e40befaa843e5b5ff3467eb5

Observation c14136a7-c4dc-4046-b233-22e8bb2b0d81 · outbound

This paper cites PLDI , year=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models PLDI , year=

Reference 4

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no resolver link, observed 2026-08-01T03:51:32.385931Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-01T03:51:32.385931Z digest=sha256:b5cf9a9f6b96a86f6e58b03b57a606d1d5b5996111d5fbea1b4815e83c88810d

Observation afec68e4-7b5c-4c86-a84a-c2a016ff38ca · outbound

This paper cites Density-Based Semantics for Reactive Probabilistic Programming.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Density-Based Semantics for Reactive Probabilistic Programming

Reference 5

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verified exact
local_arxiv, observed 2026-08-01T03:53:30.772090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-01T03:51:32.389338Z digest=sha256:47821e8629b13c2d21464155689bfc6438c9a1b500386418fa79a343d9d5b476

Observation 7b649fb4-a900-4392-92e5-93c7de4acc63 · outbound

This paper cites Advances in Variational Inference , journal =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Advances in Variational Inference , journal =

Reference 6

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no resolver link, observed 2026-08-01T03:51:32.393163Z

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source=arxiv_source observed=2026-08-01T03:51:32.393163Z digest=sha256:277f17eb03e187389d4a4166d05397df3aba42df6ad14246f2027da6e614031b

Observation 1a5fcce5-83de-42f0-a57a-f884c7a700b9 · outbound

This paper cites 2022 , url =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models 2022 , url =

Reference 7

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source=arxiv_source observed=2026-08-01T03:51:32.396408Z digest=sha256:41d5fab0ca53102fc93e569530814f55da7ef1e83708e2e84a466a2e5b023aa5

Observation 81bf36dc-859f-4d7f-a91f-9ae998a8e313 · outbound

This paper cites 2020 Design, Automation.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models 2020 Design, Automation

Reference 8

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no resolver link, observed 2026-08-01T03:51:32.399372Z

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source=arxiv_source observed=2026-08-01T03:51:32.399372Z digest=sha256:d5eb9b6c0752cfff4c98b5e40266e51b2a204b251eaa6e5bf07c75e7826703ad

Observation dc1d6c43-fd09-4b1a-84dd-2dc1c0fa1ccb · outbound

This paper cites Reproducing the Universe: a comparison between the EAGLE simulations and the nearby DustPedia galaxy sample.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Reproducing the Universe: a comparison between the EAGLE simulations and the nearby DustPedia galaxy sample

Reference 9

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Observation f716566a-1b17-4d57-a6ea-72e05fb1ee54 · outbound

This paper cites Rozier and Johann Schumann , editor =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Rozier and Johann Schumann , editor =

Reference 10

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-01T03:51:32.405780Z digest=sha256:62f4c3c60a138f28a11bd9325b4824745d326c03a996be04d029fdc1bf83bdf2

Observation fa267774-2772-4e38-8c2a-6f74892d50a7 · outbound

This paper cites an unresolved cited work.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Unresolved cited work

Reference 11

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Observation ce557da7-c10d-451c-9462-140880737598 · outbound

This paper cites Bayesian Robot Programming , journal =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Bayesian Robot Programming , journal =

Reference 12

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Observation 2987efb5-bfda-41cf-9953-ab10db316b5a · outbound

This paper cites 2013 , url=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models 2013 , url=

Reference 13

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Observation 13802134-6773-4398-b3ec-a4eee08c8170 · outbound

This paper cites 2017 , url =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models 2017 , url =

Reference 14

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no resolver link, observed 2026-08-01T03:51:32.417595Z

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source=arxiv_source observed=2026-08-01T03:51:32.417595Z digest=sha256:eb91a6680753a56a19fda01558dd6bf1719790f570a23f57b020cf4143db49ac

Observation 60ef3ac1-90c6-44c2-8378-50c3ad386387 · outbound

This paper cites Banerjee and Zbigniew T.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Banerjee and Zbigniew T

Reference 15

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Observation b7d53f97-da74-4612-9465-513bb54c7367 · outbound

This paper cites Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks , booktitle =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks , booktitle =

Reference 16

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Observation b6fb8090-ea5c-4c20-b25b-a9fd569af5c0 · outbound

This paper cites 2022 , booktitle =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models 2022 , booktitle =

Reference 17

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Observation d61358e1-539f-48ec-b5d6-c7b8e266a7d8 · outbound

This paper cites Journal of the American statistical Association , year=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Journal of the American statistical Association , year=

Reference 18

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Observation c7d15205-10cc-4f0f-8105-178e3b7ec2dd · outbound

This paper cites an unresolved cited work.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Unresolved cited work

Reference 19

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 708c76ba-b70f-475f-a2eb-4b3cdcdab338 · outbound

This paper cites an unresolved cited work.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Unresolved cited work

Reference 20

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Observation 1bb53de3-a463-48f2-9cea-7105ac4da452 · outbound

This paper cites an unresolved cited work.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Unresolved cited work

Reference 21

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 97c2ac0b-16dc-4f7a-a2c8-421e0f8bb9f5 · outbound

This paper cites an unresolved cited work.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Unresolved cited work

Reference 22

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation ce7a1691-5b8c-4ae5-b01d-5ea33434281c · outbound

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MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Design Automation Conference (DAC) , year=

Reference 23

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Observation 70a85d07-3afc-42e1-9133-f7a5ed2aa122 · outbound

This paper cites Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems,.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems,

Reference 24

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Observation 564b3f38-32f9-469a-b3b7-e1f96d03ea9e · outbound

This paper cites Deep Amortized Inference for Probabilistic Programs.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Deep Amortized Inference for Probabilistic Programs

Reference 25

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Observation 9eec71ea-2ab1-4a09-9fe8-357d6cde6e09 · outbound

This paper cites Continualization of Probabilistic Programs With Correction , booktitle =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Continualization of Probabilistic Programs With Correction , booktitle =

Reference 26

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Observation 47bfc976-8c42-4afc-b844-ec39bb87f90b · outbound

This paper cites and Henzinger, Thomas A.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models and Henzinger, Thomas A

Reference 27

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Observation b3ac178b-71f8-42df-be47-b1b8ddd91e29 · outbound

This paper cites Proceedings of the 55th Annual Design Automation Conference,.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Proceedings of the 55th Annual Design Automation Conference,

Reference 28

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Observation ed95fe27-0dd8-4ff8-a1e2-5103207be511 · outbound

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MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models arXiv: Learning , year=

Reference 29

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Observation 77a20461-fd08-4ea1-81f1-1caf42e7e7ed · outbound

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MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models An Unbiased

Reference 30

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Observation 4b87440b-1e93-48fd-8530-5b46d2c39dec · outbound

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MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models ProbLP: A framework for low-precision probabilistic inference

Reference 31

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Observation 0ba17551-2f81-4913-b95d-cedd19bd55df · outbound

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MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Neurocomputing , volume =

Reference 32

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 0c9a6bae-3974-4239-9fdd-142ad04cba88 · outbound

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MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Ko and Yuji Chai and Rob A

Reference 33

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Observation 1f6bc87c-2a73-4345-a4fd-a9ce5f4f95bf · outbound

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MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Beyond Application End-Point Results: Quantifying Statistical Robustness of MCMC Accelerators

Reference 34

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Observation 3811c70a-4f07-44d3-91e8-ff49521a4e5c · outbound

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MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models and Vainio, O

Reference 35

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Observation 1a98f5c5-9d75-4c70-8db5-e66355d87f81 · outbound

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MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Unresolved cited work

Reference 36

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Observation daa032cf-eb26-4c29-b1f2-d4bcb3435548 · outbound

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MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Vechev , editor =

Reference 37

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Observation a422f593-1c1d-4c1c-bd40-a745c5b92cab · outbound

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MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models IEEE Standard for Floating-Point Arithmetic , year=

Reference 38

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Observation 1f7d4090-a9ea-411f-94e3-6537404c3026 · outbound

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MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Compiling Stan to generative probabilistic languages and extension to deep probabilistic programming , booktitle =

Reference 39

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source=arxiv_source observed=2026-08-01T03:51:32.494048Z digest=sha256:07e44185b615c80700ca0a7a8eddb872b3d1f3958cac104ca40a6500c36063f8

Observation 5c7a8689-d5bd-4ecb-8da6-f14757cf92b8 · outbound

This paper cites Journal of Statistical Software , author=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Journal of Statistical Software , author=

Reference 40

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source=arxiv_source observed=2026-08-01T03:51:32.496900Z digest=sha256:0606d9d22aaf85b6539f2b134bc10cfbc2a601080e695aa1556d4565cdb45c26

Observation 3aca2e13-6d9d-4762-93de-292e2f22d1f6 · outbound

This paper cites Automatically improving accuracy for floating point expressions , booktitle =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Automatically improving accuracy for floating point expressions , booktitle =

Reference 41

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source=arxiv_source observed=2026-08-01T03:51:32.499870Z digest=sha256:f836c0654beaba94bb8e103e6e75323317c360c3aeb6835305e76e3a6f4b88d7

Observation fa3075ae-7cee-4f4d-8383-d4b63355a211 · outbound

This paper cites A Survey of Model Compression and Acceleration for Deep Neural Networks.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models A Survey of Model Compression and Acceleration for Deep Neural Networks

Reference 42

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source=arxiv_source observed=2026-08-01T03:51:32.502889Z digest=sha256:0605a7136669bd113cbe2c2613e0b9ab82fc2b6db4939bd748ae261fc7811285

Observation 3bfbc33f-9067-4cf0-a7eb-96cd29436630 · outbound

This paper cites and Jankowiak, Martin and Obermeyer, Fritz and Pradhan, Neeraj and Karaletsos, Theofanis and Singh, Rohit and Szerlip, Paul and Horsfall, Paul and Goodman, Noah D.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models and Jankowiak, Martin and Obermeyer, Fritz and Pradhan, Neeraj and Karaletsos, Theofanis and Singh, Rohit and Szerlip, Paul and Horsfall, Paul and Goodman, Noah D

Reference 43

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source=arxiv_source observed=2026-08-01T03:51:32.506131Z digest=sha256:c9881b63bf4d0c7303193429612360b84717e96f8eefc4027c0ff9ec76f938d3

Observation 7429e2e0-4c36-42bd-a2bd-ffadf8ea6fcf · outbound

This paper cites Deep Learning with Limited Numerical Precision , booktitle =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Deep Learning with Limited Numerical Precision , booktitle =

Reference 44

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source=arxiv_source observed=2026-08-01T03:51:32.508905Z digest=sha256:5a1e781cad73046a7e7b8032560d434d049d14f74fd15030652d96fb3226373c

Observation e9ad5e9a-64ab-478f-a91f-6f04d053bfc5 · outbound

This paper cites and Krishnan, S.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models and Krishnan, S

Reference 45

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source=arxiv_source observed=2026-08-01T03:51:32.511700Z digest=sha256:37719230f1f08f47fbd38a69d1f622837adea5bb0a295403f9cedcccb1ee1778

Observation 9d6919c7-f32c-4780-9a3a-b7a6fb9fce55 · outbound

This paper cites Fully Convolutional Networks for Semantic Segmentation.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Fully Convolutional Networks for Semantic Segmentation

Reference 46

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source=arxiv_source observed=2026-08-01T03:51:32.514642Z digest=sha256:29c400e1c2c5b1aa358f0922f393d69afb100e29b28ddce92dad640e2b85ff9b

Observation 76368900-33f3-42bd-953a-46d554eefe62 · outbound

This paper cites Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=

Reference 47

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no resolver link, observed 2026-08-01T03:51:32.518032Z

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source=arxiv_source observed=2026-08-01T03:51:32.518032Z digest=sha256:f18fe318ae1131cfe22a6ed2589765c832a41c8f3e018f15f45204cb55cd306f

Observation a553fbc3-748f-4f52-ba06-0949598618c6 · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

Reference 48

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source=arxiv_source observed=2026-08-01T03:51:32.520963Z digest=sha256:03651add61cd0f86833d1baed8fa195fb442eb7380741a2dd6a9bc85db558e57

Observation 7bc9c8a7-ca43-47b7-9d0a-ffc3a431ab75 · outbound

This paper cites Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=

Reference 49

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source=arxiv_source observed=2026-08-01T03:51:32.523710Z digest=sha256:0cbd6229f3e09ebefd5230a648362ce88e6fb9da271321a482201f21da20f9c6

Observation de4e0c92-484e-490b-9fd7-b0fd1b501a00 · outbound

This paper cites Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=

Reference 50

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source=arxiv_source observed=2026-08-01T03:51:32.526964Z digest=sha256:f157490b0a3abff574dddfb932e471351e531c0017d54be47ba3b718c12a3383

Observation 2fa08632-482e-4922-993a-f312deec7af4 · outbound

This paper cites Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision , pages=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision , pages=

Reference 51

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source=arxiv_source observed=2026-08-01T03:51:32.529880Z digest=sha256:cba4725adc025b44b7b5bdb4ee595e9edbf963a1f2b427c7fddf879ff362a65a

Observation 17b0f7f6-10fb-4ca7-8974-f6bf6b27d4ae · outbound

This paper cites Latency-Constrained Input-Aware Quantization of Time Series Inference Workflows at the Edge , year=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Latency-Constrained Input-Aware Quantization of Time Series Inference Workflows at the Edge , year=

Reference 52

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source=arxiv_source observed=2026-08-01T03:51:32.532498Z digest=sha256:33de92e67b61f38578e73ffb2555d320bedb683f0ccb7cef4ebd5be13db13e7b

Observation c66365a9-07bd-479b-a5fe-70388dd6f06a · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

Reference 53

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source=arxiv_source observed=2026-08-01T03:51:32.535149Z digest=sha256:1850041f53f136c87b6f5f38760d16e6a1096a67e7c156b10a2f6b6eaed69f0b

Observation 9fc233a0-d067-429d-b244-705bfa6fec08 · outbound

This paper cites International Conference on Machine Learning , pages=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models International Conference on Machine Learning , pages=

Reference 54

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source=arxiv_source observed=2026-08-01T03:51:32.537811Z digest=sha256:9eea380d536870eb91e70af5e4132949daae0b94aaebc4bd24d0e5d9f1baab8f

Observation 1212c852-a1c9-4fc8-a945-efc2b6935824 · outbound

This paper cites Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=

Reference 55

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source=arxiv_source observed=2026-08-01T03:51:32.540734Z digest=sha256:da7a830fc25f546336fd572e94e2900aae1fe8da02e4194bb8eb9ee31b746c8f

Observation d8e6dbc9-98ea-4f44-8c68-32725749331f · outbound

This paper cites NeurIPS ML for Systems workshop, 2018 , year=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models NeurIPS ML for Systems workshop, 2018 , year=

Reference 56

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source=arxiv_source observed=2026-08-01T03:51:32.543398Z digest=sha256:26a7d31092c143057ce5289c4219207577005f9479323a17b87e28921cb7a7cf

Observation 99828d29-e5ef-4b53-a7c9-75490d53fb1c · outbound

This paper cites Le , title =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Le , title =

Reference 57

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source=arxiv_source observed=2026-08-01T03:51:32.546133Z digest=sha256:f15e87251c1a73d922bf128cb199451488255cec9da2e0bd6f2eb6cd6da03cea

Observation 3908fbf6-5a21-41fb-ad82-16f8468af5be · outbound

This paper cites Search What You Want: Barrier Panelty.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Search What You Want: Barrier Panelty

Reference 58

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verified exact
doi, observed 2026-08-01T03:53:28.340629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-01T03:51:32.548874Z digest=sha256:f0d3e986c29afe3f184e831b7d3a254634d4d42f4cecca420453c91b037599b9

Observation 68d9a3d3-decb-448b-8117-969454cf0ac7 · outbound

This paper cites 2021 , url =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models 2021 , url =

Reference 59

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source=arxiv_source observed=2026-08-01T03:51:32.551569Z digest=sha256:f1572f7fe3272882d0d29575250c9afe60be13d8c7a2c9c22bb57f3301bb28a3

Observation e3a4b47b-7430-493b-9b32-4f0243a290d6 · outbound

This paper cites Mixed Precision Quantization of ConvNets via Differentiable Neural Architecture Search.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Mixed Precision Quantization of ConvNets via Differentiable Neural Architecture Search

Reference 60

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source=arxiv_source observed=2026-08-01T03:51:32.554163Z digest=sha256:5952c3e182e6490093aa0a2f6180c0f407644f23b08ddfed43f0ec8fc3dbb74e

Observation 4f54b718-8955-486b-b384-f159a0021282 · outbound

This paper cites Temporal Dynamic Quantization for Diffusion Models , booktitle =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Temporal Dynamic Quantization for Diffusion Models , booktitle =

Reference 61

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source=arxiv_source observed=2026-08-01T03:51:32.557091Z digest=sha256:994825f949a20afec72159a9113d51801f32e61a27b275dd18661a2a47782b8e

Observation 1442787c-5840-4495-8254-97e4ae2bfc12 · outbound

This paper cites Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=

Reference 62

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source=arxiv_source observed=2026-08-01T03:51:32.559727Z digest=sha256:472c310d25a61529aaaf379d957c60d392abb85f0f22e2c92a129aab08d385ed

Observation 1bdbd0b5-7c40-4c1c-90fa-81e91607846b · outbound

This paper cites European Conference on Computer Vision , pages=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models European Conference on Computer Vision , pages=

Reference 63

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source=arxiv_source observed=2026-08-01T03:51:32.562440Z digest=sha256:00d45cfa8ebddd297eea26a62e4ed82051b6dcbfce721ad40c43c963ca681a43

Observation a9fb9406-5774-4738-b870-b62e0220919c · outbound

This paper cites an unresolved cited work.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Unresolved cited work

Reference 64

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doi, observed 2026-08-01T03:53:28.111793Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-01T03:51:32.565303Z digest=sha256:f52e6c201d76a789458d2544d4df25e7800819c390fb77ba1ba86d8c7b9213ea

Observation dbdc84b7-d2ac-4479-adf6-6fa3a91f832b · outbound

This paper cites 2022 , url =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models 2022 , url =

Reference 65

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source=arxiv_source observed=2026-08-01T03:51:32.568016Z digest=sha256:06117613c19b19d2ff59794622fd6210541ad533f49ee18d426d0084139f15ee

Observation abfeeef1-441f-49ef-8569-d77ff42750c2 · outbound

This paper cites Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation , pages=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation , pages=

Reference 66

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source=arxiv_source observed=2026-08-01T03:51:32.570551Z digest=sha256:5fbd58c024147910f6ddf62c09f0f10e2acc6e78355b653a80d23271ccc16631

Observation 93c584c7-2a11-425f-a2d7-3c49bbe37f69 · outbound

This paper cites Robust Quantization: One Model to Rule Them All.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Robust Quantization: One Model to Rule Them All

Reference 67

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source=arxiv_source observed=2026-08-01T03:51:32.573173Z digest=sha256:cc6a84f8fa96f516d0368dc899598e1906052258422876e10859213632457c35

Observation 6c0ac780-7752-480a-b920-63d0a6f8a4c0 · outbound

This paper cites MultiQuant: Training Once for Multi-bit Quantization of Neural Networks , url =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models MultiQuant: Training Once for Multi-bit Quantization of Neural Networks , url =

Reference 68

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-01T03:51:32.575906Z digest=sha256:463a8c336757bf06dc9217143b48dd348dbd189e309839a27f91ede000c1c7aa

Observation eaecd5b9-d5ad-4cc0-a998-27044ed494e7 · outbound

This paper cites Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks , booktitle =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks , booktitle =

Reference 69

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source=arxiv_source observed=2026-08-01T03:51:32.578661Z digest=sha256:4bb614d285942f82fea9db944a3b62b54c1c542cbb0bcc80fd75cbf532934392

Observation cfd4735d-d734-4612-9c87-4058111c2903 · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 70

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source=arxiv_source observed=2026-08-01T03:51:32.581279Z digest=sha256:f7c7a254eb2fd6e7e2b0ab4290ce5d17dbaf45c79ebcc101853fe9a182ce51e5

Observation 210a3200-4c70-4a10-9424-6d0900b523e8 · outbound

This paper cites Classification of Radar Targets using Features Based on Warped Discrete Fourier Transform , url =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Classification of Radar Targets using Features Based on Warped Discrete Fourier Transform , url =

Reference 71

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source=arxiv_source observed=2026-08-01T03:51:32.584405Z digest=sha256:15a1571deee1a3a824e4e8175e81ff4adefcbbed6361ff4ac4e2653b928fb94a

Observation 2cff81bb-0999-4b8d-a4cd-0a7f734ca3ec · outbound

This paper cites , author=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models , author=

Reference 72

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source=arxiv_source observed=2026-08-01T03:51:32.587073Z digest=sha256:fdfde11e053ac5ad69e34b58d181016b3bc7b7b4f29d9682ce1646aaaf2e91eb

Observation f5e16c7a-b2dd-41db-b466-50a908b7af55 · outbound

This paper cites an unresolved cited work.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Unresolved cited work

Reference 73

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verified exact
doi, observed 2026-08-01T03:53:27.584491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-01T03:51:32.589760Z digest=sha256:053627b55f2717cc8673f15f2991ab22ccd397706bf915121531a3ef1217ed5d

Observation 3f077559-c12e-452c-8e20-ff91d8ea76c3 · outbound

This paper cites Progressive Neural Compression for Adaptive Image Offloading Under Timing Constraints , url=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Progressive Neural Compression for Adaptive Image Offloading Under Timing Constraints , url=

Reference 74

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source=arxiv_source observed=2026-08-01T03:51:32.592460Z digest=sha256:f39b8220e31d8c056fcffa891717a7b7d8eb1934d67866064f9b5f97a6650a42

Observation dd388dfd-681f-4d20-a8c8-60a4bf120bdf · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 75

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.595215Z digest=sha256:abcfdb332109b336c98299ae4aaa33e1d4371c2b9de1e5d7b2f2afb8c5635f37

Observation b9d66156-0194-46d0-95bc-8d96d2fee6d9 · outbound

This paper cites and Zhu, Menglong and Zhmoginov, Andrey and Chen, Liang-Chieh , title =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models and Zhu, Menglong and Zhmoginov, Andrey and Chen, Liang-Chieh , title =

Reference 76

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source=arxiv_source observed=2026-08-01T03:51:32.598223Z digest=sha256:dd9c0c31642b6f6a03a907b6dc717c9234b75cd9c4c5a597f52199734a741a38

Observation 2918f401-5f66-4263-9dee-00a962d5169d · outbound

This paper cites and Adam, Hartwig , title =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models and Adam, Hartwig , title =

Reference 77

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source=arxiv_source observed=2026-08-01T03:51:32.600960Z digest=sha256:d3c82f5d7bb09af2482fb5c8560296efb404ba5b40dd6442da287eda050875ab

Observation 8bde1069-e876-480a-944c-57a4665fec21 · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 78

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unresolved
no resolver link, observed 2026-08-01T03:51:32.603514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.603514Z digest=sha256:12e1ffa35cdc5b08641b9582ead93f6645787573818c0c9af88f90fbd8edee07

Observation 18e3d349-bc72-4f68-8f97-6cdd39782a73 · outbound

This paper cites 2024 33rd International Conference on Computer Communications and Networks (ICCCN) , pages=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models 2024 33rd International Conference on Computer Communications and Networks (ICCCN) , pages=

Reference 79

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unresolved
no resolver link, observed 2026-08-01T03:51:32.606423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.606423Z digest=sha256:5281fc63c3e44edf674ffd4d0fca1b70278d11565cd2af68f8725f295e729613

Observation 995c3780-315b-4938-9eb3-df9ea9b297e9 · outbound

This paper cites Advances in Neural Information Processing Systems , year =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Advances in Neural Information Processing Systems , year =

Reference 80

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unresolved
no resolver link, observed 2026-08-01T03:51:32.609187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.609187Z digest=sha256:29af6860e527ceda070a77876cb82fd3eb4f623e36db143eb44baae292678566

Observation 696bfb10-07b2-4100-b69a-a2a0995c8923 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Adam: A Method for Stochastic Optimization

Reference 81

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unresolved
no resolver link, observed 2026-08-01T03:51:32.611803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.611803Z digest=sha256:2c2f9fa4d88d34761ed10207a72db7d44f9f39a4a1188f735132cbe1b91d1507

Observation 97488244-4a8e-4cb4-88e6-4fab2ae35d32 · outbound

This paper cites DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients

Reference 82

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unresolved
no resolver link, observed 2026-08-01T03:51:32.614688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.614688Z digest=sha256:113b1c8b8ec7cbdf69080b1b6c0eaf58b1ff1a0a1842a8c4675e49dd68cd1e3e

Observation bbd8263a-a2c0-4c32-bfb7-b215b89d7876 · outbound

This paper cites PACT: Parameterized Clipping Activation for Quantized Neural Networks.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models PACT: Parameterized Clipping Activation for Quantized Neural Networks

Reference 83

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unresolved
no resolver link, observed 2026-08-01T03:51:32.617782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.617782Z digest=sha256:d81c45517577c29155e892e3863aa53400057657952b31a8f3bd37ce0a7abe3e

Observation 434502ee-95ff-4306-b3a8-e3e5132ad50a · outbound

This paper cites Hard Sample Matters a Lot in Zero-Shot Quantization.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Hard Sample Matters a Lot in Zero-Shot Quantization

Reference 84

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metadata mismatch
local_arxiv, observed 2026-08-01T03:53:27.367236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-01T03:51:32.620646Z digest=sha256:4d124ccecd566444947b8ef361a79f9f1c6250616eb57c44f0d6f80ee99b8d20

Observation 3e8ae0d5-6218-4384-b3f0-6f9268a47943 · outbound

This paper cites Proceedings of the 21st ACM Conference on Embedded Networked Sensor Systems , pages=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Proceedings of the 21st ACM Conference on Embedded Networked Sensor Systems , pages=

Reference 85

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no resolver link, observed 2026-08-01T03:51:32.623495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.623495Z digest=sha256:c3d74cfaafeae8cf276150d50308f58ce37901ce062b0309540e66e0a6bba1db

Observation e5ec6c4f-f4a8-4632-9a67-5553b9f11404 · outbound

This paper cites 2024 33rd International Conference on Computer Communications and Networks (ICCCN) , pages=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models 2024 33rd International Conference on Computer Communications and Networks (ICCCN) , pages=

Reference 86

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unresolved
no resolver link, observed 2026-08-01T03:51:32.626147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.626147Z digest=sha256:e5a087ffcb76c96cff24321ee6afbbfc3e92e59828c9a3ec770ec07518e9cb00

Observation d1741d34-8e0a-4b6c-a726-d57b39c6326a · outbound

This paper cites Proceedings of the ACM on Web Conference 2024 , pages=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Proceedings of the ACM on Web Conference 2024 , pages=

Reference 87

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unresolved
no resolver link, observed 2026-08-01T03:51:32.628938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.628938Z digest=sha256:fffc9b96e72e940228cbb043aa14e5cbf7dd3415ae90a90d1ed77e8256ad0860

Observation 6f16d394-a09d-46b6-a954-18ebf2dbddc5 · outbound

This paper cites an unresolved cited work.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Unresolved cited work

Reference 88

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unresolved
no resolver link, observed 2026-08-01T03:51:32.631715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.631715Z digest=sha256:1f752b2097302d45142f146c672d6ddf62f9544986a248c8c8a02b093cb3be26

Observation f188ebce-64fa-4c6f-8c09-965dbaab8d22 · outbound

This paper cites Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=

Reference 89

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no resolver link, observed 2026-08-01T03:51:32.634251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.634251Z digest=sha256:072e8a4a815358e0163fb239b02202f4d447a6695927360c1707e087ab3cbf2e

Observation d27db97e-eec6-4031-968d-c1e19e43208e · outbound

This paper cites an unresolved cited work.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Unresolved cited work

Reference 90

Resolution
verified exact
doi, observed 2026-08-01T03:53:27.234846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-01T03:51:32.636848Z digest=sha256:ef6d47aab0194b9f0fb29e684f68f8e020554887bddfe326fc9683151f6af0e7

Observation d52c2a5a-da13-48e0-9a6b-8457fbc1ddb4 · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

Reference 91

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unresolved
no resolver link, observed 2026-08-01T03:51:32.639636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.639636Z digest=sha256:4e61f632b27caf6f4dfd6290796cedc3c0cfba8a1c236e1c9f8d1e7f12e60e5f

Observation 7495ec3a-6fc1-4902-841b-79f6b2665059 · outbound

This paper cites an unresolved cited work.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Unresolved cited work

Reference 92

Resolution
verified exact
doi, observed 2026-08-01T03:53:27.115574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-01T03:51:32.642445Z digest=sha256:a4e8b755682c6139d07b81df36be982e877c50a909f18c6efc0bd65ca3565408

Observation be4dcddd-8248-469d-8fc4-8a508d58fdf2 · outbound

This paper cites an unresolved cited work.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Unresolved cited work

Reference 93

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parse uncertain
no resolver link, observed 2026-08-01T03:51:32.645591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.645591Z digest=sha256:530b27bb661629b0a71a63e232d1161571274cf467f51aa1322fdcc5a213ad73

Observation 3565674b-bcb7-43b3-b56f-b8ef258b7433 · outbound

This paper cites Triton: an intermediate language and compiler for tiled neural network computations , booktitle =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Triton: an intermediate language and compiler for tiled neural network computations , booktitle =

Reference 94

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unresolved
no resolver link, observed 2026-08-01T03:51:32.648507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.648507Z digest=sha256:7d58a0189f32a293293687c7c1c45319ce5142281efcf85d8859d1f2725431a1

Observation bdb35515-9976-49ef-9a92-2661b16a90d7 · outbound

This paper cites an unresolved cited work.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Unresolved cited work

Reference 95

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unresolved
no resolver link, observed 2026-08-01T03:51:32.651381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.651381Z digest=sha256:7af678b3479e3639d0301de37b17d33781db4400d64072a13e48667e4c49b55a

Observation 32808eaf-1304-4e5e-aefc-defcc1e3c61b · outbound

This paper cites Compressing Deep Convolutional Networks using Vector Quantization.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Compressing Deep Convolutional Networks using Vector Quantization

Reference 96

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unresolved
no resolver link, observed 2026-08-01T03:51:32.653950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.653950Z digest=sha256:a628d7331848c66e204c7c8de05951cbb2457c27312926df408d1c87a889a3eb

Observation c91577dc-6707-4f69-9160-3f2740e60d8d · outbound

This paper cites Gray , title =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Gray , title =

Reference 97

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unresolved
no resolver link, observed 2026-08-01T03:51:32.656984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.656984Z digest=sha256:34965216cf1e1dca405f0b0ab4243a1c3a8d3700fc0da975bd5d876ee75987c5

Observation e79d920c-b3ab-4eb9-9c4e-a06f2dc724f7 · outbound

This paper cites , journal=.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models , journal=

Reference 98

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unresolved
no resolver link, observed 2026-08-01T03:51:32.659671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:51:32.659671Z digest=sha256:9e810f937c89d864fc63f42c146262cbae08a7c1aef63ceba9d72ed4488118ab

Observation 882877b9-5906-412d-8f63-2bd237636d12 · outbound

This paper cites an unresolved cited work.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Unresolved cited work

Reference 99

Resolution
verified exact
doi, observed 2026-08-01T03:53:26.805338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-01T03:51:32.662363Z digest=sha256:dc19a1be81ecc64d97e015c8b50262c9bcfc56555ce0642b4791aca4a6c48c7b

Observation 56db09d3-2335-4a13-b824-14e90910ae77 · outbound

This paper cites Sensors , volume =.

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models Sensors , volume =

Reference 100

Resolution
verified exact
doi, observed 2026-08-01T03:53:26.536995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-01T03:51:32.664993Z digest=sha256:335d769047f60374a8a3b54f38eda91f2db70fdd2417cec73bbc98fb1a2b422b

Pith citing papers

No inbound Pith citation observations are available.