Paper Citation Record · LEDGER

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats

As of 15 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 2 inbound Pith citation observations for arXiv:2606.04115.

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

pith.paper-citation-record.v1
2606.04115 v2

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-15T10:56:54.155632Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T07:54:47.701071Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

47 of 47 outbound references displayed

verified exact0
verified fuzzy0
unresolved46
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ad2f2e7d-cf85-4525-b6c6-90bddde7b417 · outbound

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

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation ee30ae9b-ca06-4ee9-b672-3f21a2953f96 · outbound

This paper cites AWQ: Activation-aware weight quantization for on-device LLM compression and acceleration.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats AWQ: Activation-aware weight quantization for on-device LLM compression and acceleration

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 01a4e7a5-eb51-4815-adf9-1e6d577bd502 · outbound

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

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats SmoothQuant: Accurate and efficient post-training quantization for large language models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 9278231b-8ec9-4fc8-a0cb-8329141765f4 · outbound

This paper cites FP8 versus INT8 for efficient deep learning inference.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats FP8 versus INT8 for efficient deep learning inference

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 481d94f3-5b30-4a98-b9f7-de44a7593944 · outbound

This paper cites Microscaling Data Formats for Deep Learning.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Microscaling Data Formats for Deep Learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 93c15a61-5ed5-4e82-81bf-e6fad0f6021c · outbound

This paper cites OCP microscaling formats (MX) specification.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats OCP microscaling formats (MX) specification

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation db86112b-4290-4684-899a-0786cffaca66 · outbound

This paper cites Castro, Denis Kuznedelev, Andrei Panferov, Eldar Kurtic, Shubhra Pandit, Alexandre Marques, Mark Kurtz, Saleh Ashkboos, Torsten Hoefler, and Dan Alistarh.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Castro, Denis Kuznedelev, Andrei Panferov, Eldar Kurtic, Shubhra Pandit, Alexandre Marques, Mark Kurtz, Saleh Ashkboos, Torsten Hoefler, and Dan Alistarh

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 1c0758d5-1a34-4f28-a2f0-20785ac3b287 · outbound

This paper cites Pushing the Limits of Block Rotations in Post-Training Quantization.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Pushing the Limits of Block Rotations in Post-Training Quantization

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation ab19d72d-a88c-444d-ac8a-d5061e50152c · outbound

This paper cites Gradient-free training of quantized neural networks.arXiv preprint arXiv:2410.09734, 2024.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Gradient-free training of quantized neural networks.arXiv preprint arXiv:2410.09734, 2024

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation c518c453-cef8-44b6-81de-20f6f8beec97 · outbound

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

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Mixed Precision Quantization of ConvNets via Differentiable Neural Architecture Search

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 6549b819-c731-416b-bf69-6dd520ea3759 · outbound

This paper cites InfoQ: Mixed-precision quantization via global information flow.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats InfoQ: Mixed-precision quantization via global information flow

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation bf4d76be-c080-4b2d-9236-d0604f2a54b7 · outbound

This paper cites Mix-QSAM: Mixed-precision quantization of the segment anything model.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Mix-QSAM: Mixed-precision quantization of the segment anything model

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 08fc48cc-320a-482d-8498-3310774cc854 · outbound

This paper cites Mahoney, and Kurt Keutzer.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Mahoney, and Kurt Keutzer

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 1643021f-e6ed-4749-98ba-6c151a89588f · outbound

This paper cites Mahoney, and Kurt Keutzer.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Mahoney, and Kurt Keutzer

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 7c646271-eefb-491d-8b1b-b9ce184dc32b · outbound

This paper cites FracBits: Mixed precision quantization via fractional bit-widths.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats FracBits: Mixed precision quantization via fractional bit-widths

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 6fe206fe-0942-48be-8593-3ff7846ecb38 · outbound

This paper cites SDQ: Stochastic differentiable quantization with mixed precision.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats SDQ: Stochastic differentiable quantization with mixed precision

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 19daa9d3-7fdc-4aa8-b93f-a7309fd79afa · outbound

This paper cites BSQ: Exploring bit-level sparsity for mixed-precision neural network quantization.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats BSQ: Exploring bit-level sparsity for mixed-precision neural network quantization

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation cc6f69d7-5571-4f37-81e3-abd265593efe · outbound

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

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation a434e32c-6ecf-4863-8ea6-b9cfc6d9fd30 · outbound

This paper cites SpinQuant: LLM quantization with learned rotations.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats SpinQuant: LLM quantization with learned rotations

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation d7d612a4-e4ea-4e67-87e4-9cb38f897235 · outbound

This paper cites FP8 Formats for Deep Learning.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats FP8 Formats for Deep Learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 9d22b41c-d9de-467f-bbf7-03c1fdeb3fa1 · outbound

This paper cites The Llama 3 Herd of Models.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats The Llama 3 Herd of Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 2d9dfe9b-da9c-4878-97f4-990864d39101 · outbound

This paper cites Qwen3 Technical Report.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Qwen3 Technical Report

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 23221f78-ef63-498a-896a-112aaeb2f0c5 · outbound

This paper cites SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 39fc2f7e-39a6-4012-8bd0-83889c053788 · outbound

This paper cites The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation da55252b-2d7e-4545-b41f-7833a312284d · outbound

This paper cites Pointer sentinel mixture models.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Pointer sentinel mixture models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 9d153449-e1ac-486a-92bb-8d07f182e904 · outbound

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

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 0cd6ab72-3a53-4873-b04e-f88a3b0e613b · outbound

This paper cites HellaSwag: Can a machine really finish your sentence? InProceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats HellaSwag: Can a machine really finish your sentence? InProceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 003985f4-3b25-4b5d-80e7-de8a740a3f5b · outbound

This paper cites WinoGrande: An adversarial Winograd schema challenge at scale.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats WinoGrande: An adversarial Winograd schema challenge at scale

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 16bb2e4a-95a1-4fa8-9132-86d0a3aa8f71 · outbound

This paper cites LightEval: A lightweight framework for LLM evaluation, 2023.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats LightEval: A lightweight framework for LLM evaluation, 2023

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation d601c840-e235-4b08-99dd-ec3d9529dae1 · outbound

This paper cites Xilinx/brevitas, 2025.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Xilinx/brevitas, 2025

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation ed56cbed-bca2-42c5-bca4-78b413f7aead · outbound

This paper cites HAQ: Hardware-aware automated quantization with mixed precision.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats HAQ: Hardware-aware automated quantization with mixed precision

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

Source-reported events for the cited work

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Observation 48f2a0df-601f-4909-b6f3-0a5c51f33691 · outbound

This paper cites Mahoney, and Kurt Keutzer.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Mahoney, and Kurt Keutzer

Reference 32

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 7f4fbf9b-d0ac-4ec0-bd2f-40fafd3a5417 · outbound

This paper cites Towards mixed-precision quantization of neural networks via constrained optimization.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Towards mixed-precision quantization of neural networks via constrained optimization

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 4fac3b13-23c5-4ecd-b57b-956ee215fab9 · outbound

This paper cites APTQ: Attention- aware post-training mixed-precision quantization for large language models.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats APTQ: Attention- aware post-training mixed-precision quantization for large language models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 74e42f0f-80a9-4853-899d-dc176c6a364d · outbound

This paper cites ResQ: Mixed-Precision Quantization of Large Language Models with Low-Rank Residuals.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats ResQ: Mixed-Precision Quantization of Large Language Models with Low-Rank Residuals

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 08cd2662-885c-4a08-aefa-9a18558cccb4 · outbound

This paper cites Rethinking differentiable search for mixed-precision neural networks.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Rethinking differentiable search for mixed-precision neural networks

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation a7f2ba69-2e4f-4f6a-9051-69c02e0e1e90 · outbound

This paper cites Q-ViT: Fully Differentiable Quantization for Vision Transformer.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Q-ViT: Fully Differentiable Quantization for Vision Transformer

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

Source-reported events for the cited work

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Observation bde7d15b-b770-4eb4-86f7-c99623cd7404 · outbound

This paper cites Jennings, and Arnon Netzer.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Jennings, and Arnon Netzer

Reference 38

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 661e2b61-8681-47a3-b38e-7d6d9a005ae8 · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Categorical Reparameterization with Gumbel-Softmax

Reference 39

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 7b0a9cef-c448-460e-8b09-dfe8ee63a201 · outbound

This paper cites Maddison, Andriy Mnih, and Yee Whye Teh.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Maddison, Andriy Mnih, and Yee Whye Teh

Reference 40

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

Source-reported events for the cited work

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Observation ee03602b-45d2-4e47-be90-6742f83b1812 · outbound

This paper cites Bayesian bits: Unifying quantization and pruning.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Bayesian bits: Unifying quantization and pruning

Reference 41

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 071a89b9-b2e8-4bf8-9409-5df2ed95db63 · outbound

This paper cites Mixed precision DNNs: All you need is a good parametrization.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Mixed precision DNNs: All you need is a good parametrization

Reference 42

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 9f154de3-d264-4d0b-85a0-0d9a09ac4ec0 · outbound

This paper cites Micromix: Efficient mixed-precision quantization with microscaling formats for large language models.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Micromix: Efficient mixed-precision quantization with microscaling formats for large language models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 1706284e-6580-47a0-8ce0-69f1fa70e68b · outbound

This paper cites Mixture compressor for mixture-of-experts LLMs gains more.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Mixture compressor for mixture-of-experts LLMs gains more

Reference 44

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 8729cef7-133b-4cbb-8482-b21842caaf08 · outbound

This paper cites Ieee standard for floating-point arithmetic.IEEE Std 754-2019 (Revision of IEEE 754-2008), pages 1–84, 2019.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Ieee standard for floating-point arithmetic.IEEE Std 754-2019 (Revision of IEEE 754-2008), pages 1–84, 2019

Reference 45

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation 94e0abd4-2429-4786-a96d-5360e50e7183 · outbound

This paper cites Jain, Albert Gural, Michael Wu, and Chris H.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats Jain, Albert Gural, Michael Wu, and Chris H

Reference 46

Resolution: unresolved; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Observation a0ec5a63-2236-4959-bb80-e4552ea9db58 · outbound

This paper cites PyTorch: An imperative style, high-performance deep learning library.

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats PyTorch: An imperative style, high-performance deep learning library

Reference 47

Resolution: malformed identifier; no resolver link, observed 2026-07-15T10:56:54.155632Z

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Pith citing papers

Observation f96a24be-7752-4512-886e-858bc8952ebf · inbound

Variable Bit-width Quantization: Learning Per-Group Precision for "Bigger-but-Smaller" Language Models cites this paper.

Variable Bit-width Quantization: Learning Per-Group Precision for "Bigger-but-Smaller" Language Models dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-12T06:20:07.112455Z

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Observation 28b9e92a-8fe5-4357-9de0-46d12ef0d38e · inbound

Reference Traces for Auditing Invisible Weight Updates and Guiding Exact-Budget Protection cites this paper.

Reference Traces for Auditing Invisible Weight Updates and Guiding Exact-Budget Protection dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-02T07:54:47.701071Z

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