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Paper Citation Record · LEDGER

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization

As of 9 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 2 inbound Pith citation observations for arXiv:2505.18113.

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

pith.paper-citation-record.v1
2505.18113 v2

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:42:14.965641Z

measured 64 of 64 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T17:34:20.870403Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-02T23:57:29.099755Z

Reference resolution

62 of 62 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dad3640b-bc80-4a3a-b8ed-8a71087d185c · outbound

This paper cites Mirror descent view for neural network quantization.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Mirror descent view for neural network quantization

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 8b896b88-d54c-434c-9635-f4df739756e7 · outbound

This paper cites Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f90159ce-80b8-4dae-a646-ec7203e81a9d · outbound

This paper cites A simple proof of the restricted isometry property for random matrices.Constructive approximation, 28:253–263, 2008.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization A simple proof of the restricted isometry property for random matrices.Constructive approximation, 28:253–263, 2008

Reference 3

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Source-reported events for the cited work

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Observation a5c5b002-e496-4d74-9fba-40911dbb3ac0 · outbound

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

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1273aab5-e590-4be4-b9cf-1e097b5a343c · outbound

This paper cites 1-bit compressive sensing.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization 1-bit compressive sensing

Reference 5

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Source-reported events for the cited work

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Observation ca68411c-2f30-4b37-92d1-4a63e4592305 · outbound

This paper cites Deep learning with low precision by half-wave gaussian quantization.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Deep learning with low precision by half-wave gaussian quantization

Reference 6

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation feb501b3-454a-4a58-b283-8229a22c2bd1 · outbound

This paper cites Robust uncertainty princi- ples: Exact signal reconstruction from highly incomplete frequency information.IEEE Transactions on information theory, 52(2):489–509, 2006.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Robust uncertainty princi- ples: Exact signal reconstruction from highly incomplete frequency information.IEEE Transactions on information theory, 52(2):489–509, 2006

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 570b4c39-5a82-49ff-8fd9-7be2620d9b6c · outbound

This paper cites Optimal Quantized Compressed Sensing via Projected Gradient Descent.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Optimal Quantized Compressed Sensing via Projected Gradient Descent

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 4d418314-df60-4e7b-8ccf-e8f8386850be · outbound

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

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization PACT: Parameterized Clipping Activation for Quantized Neural Networks

Reference 9

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Observation dd74a95a-b807-4295-8c9a-ae1a22659512 · outbound

This paper cites Ergodic theory: with a view towards number theory.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Ergodic theory: with a view towards number theory

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 73053060-d05c-44d1-8c92-c61e9e73fa73 · outbound

This paper cites Demystifying and generalizing binaryconnect.Advances in Neural Information Processing Systems, 34:13202–13216, 2021.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Demystifying and generalizing binaryconnect.Advances in Neural Information Processing Systems, 34:13202–13216, 2021

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 342cc9b5-edb4-435f-a1dd-a607123f488f · outbound

This paper cites Compressed sensing: theory and applications.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Compressed sensing: theory and applications

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 7c206f92-d001-41ef-919c-e4b03d5374e7 · outbound

This paper cites Springer, 2013.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Springer, 2013

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 297b94c4-b9f5-4ae7-8831-029c164e7b44 · outbound

This paper cites Nbiht: An efficient algorithm for 1-bit compressed sensing with optimal error decay rate.IEEE Transactions on Information Theory, 68(2):1157–1177, 2021.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Nbiht: An efficient algorithm for 1-bit compressed sensing with optimal error decay rate.IEEE Transactions on Information Theory, 68(2):1157–1177, 2021

Reference 14

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Observation 4be6af32-82a9-4b32-b043-50716afe58c8 · outbound

This paper cites Approximation of functions with one-bit neural networks.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Approximation of functions with one-bit neural networks

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 0f706f7a-3bd7-4730-a44d-41397f5041aa · outbound

This paper cites Deep residual learning for image recognition.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Deep residual learning for image recognition

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 79bc5671-2cc5-4b5a-87bc-e509acd11cc4 · outbound

This paper cites Neural networks for machine learning, coursera.Coursera, video lectures, 2012.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Neural networks for machine learning, coursera.Coursera, video lectures, 2012

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation d6406eee-dd6a-44da-8922-17ae5912f3aa · outbound

This paper cites Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

Reference 18

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Observation 939b4872-7c26-41fb-83d0-87d91f611cbc · outbound

This paper cites Quantized neural networks: Training neural networks with low precision weights and activations.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Quantized neural networks: Training neural networks with low precision weights and activations

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 51acbacb-f203-485b-b1d0-8f04eeb14ff0 · outbound

This paper cites Robust 1- bit compressive sensing via binary stable embeddings of sparse vectors.IEEE transactions on information theory, 59(4):2082–2102, 2013.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Robust 1- bit compressive sensing via binary stable embeddings of sparse vectors.IEEE transactions on information theory, 59(4):2082–2102, 2013

Reference 20

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation a9415fcd-067b-4bd5-b016-43c427b1676c · outbound

This paper cites Categorical reparameterization with gumbel- softmax.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Categorical reparameterization with gumbel- softmax

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 0bfbcbc4-2f73-4469-a03b-440b4a79ade2 · outbound

This paper cites PARQ: Piecewise-Affine Regularized Quantization.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization PARQ: Piecewise-Affine Regularized Quantization

Reference 22

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Observation 3f9b9a35-2ff7-4119-9ec3-01ede863731c · outbound

This paper cites BinaryDuo: Reducing Gradient Mismatch in Binary Activation Network by Coupling Binary Activations.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization BinaryDuo: Reducing Gradient Mismatch in Binary Activation Network by Coupling Binary Activations

Reference 23

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verified exact
local_arxiv, observed 2026-08-07T14:42:15.409987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 20fbd790-c377-4d57-8912-75d7bc682ca0 · outbound

This paper cites Imagenet classification with deep convolutional neural networks.Communications of the ACM, 60(6):84–90, 2017.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Imagenet classification with deep convolutional neural networks.Communications of the ACM, 60(6):84–90, 2017

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:42:12.234296Z digest=sha256:5d26025919e43fb7b330675046a943522f27ce25d25fc303b2f4e106e66e217d

Observation e229ef63-d85f-46a6-a29d-be984328a953 · outbound

This paper cites Gradient estimation for binary latent variables via gradient variance clipping.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Gradient estimation for binary latent variables via gradient variance clipping

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-07T14:42:19.063045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:12.303219Z digest=sha256:12a2bf3eae36761cab8abd39a923d9ae1372f31692fb9332693e58c884765cbe

Observation bbcd6625-3eb4-410e-b153-a730b075bea8 · outbound

This paper cites Gradient-based learning applied to document recognition.Proceedings of the IEEE, 86(11):2278–2324, 1998.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Gradient-based learning applied to document recognition.Proceedings of the IEEE, 86(11):2278–2324, 1998

Reference 26

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Unavailable: canonical work link unavailable.

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Observation af5693a3-a400-49a2-901e-d1c85859f7cf · outbound

This paper cites Training quantized nets: A deeper understanding.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Training quantized nets: A deeper understanding

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 81ee67b6-5af1-4dd0-b0d3-aa8402d8fafe · outbound

This paper cites Binary quantized network training with sharpness-aware minimization.Journal of Scientific Computing, 94(1):16, 2023.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Binary quantized network training with sharpness-aware minimization.Journal of Scientific Computing, 94(1):16, 2023

Reference 28

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raw_fallback, observed 2026-08-07T14:42:18.627435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation d322cc3f-6474-41b9-ae23-69436b7875b2 · outbound

This paper cites Learning quantized neural nets by coarse gradient method for nonlinear classification.Research in the Mathematical Sciences, 8:1–19, 2021.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Learning quantized neural nets by coarse gradient method for nonlinear classification.Research in the Mathematical Sciences, 8:1–19, 2021

Reference 29

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raw_fallback, observed 2026-08-07T14:42:18.473510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 74c7b00b-fb43-474c-afa7-19cb65a4bfda · outbound

This paper cites Recurrence of optimum for training weight and activation quantized networks.Applied and Computational Harmonic Analysis, 62:41–65, 2023.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Recurrence of optimum for training weight and activation quantized networks.Applied and Computational Harmonic Analysis, 62:41–65, 2023

Reference 30

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raw_fallback, observed 2026-08-07T14:42:18.293415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation a2f3827b-30ff-40a8-9a97-0e45cf356803 · outbound

This paper cites Enhance the visual representation via discrete adversarial training.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Enhance the visual representation via discrete adversarial training

Reference 31

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raw_fallback, observed 2026-08-07T14:42:18.097482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 53ad7dd1-bfe2-477a-9597-d5d55b2cc5c9 · outbound

This paper cites Binary iterative hard thresholding converges with optimal number of measurements for 1-bit compressed sensing.Journal of the ACM, 71(5):1–64, 2024.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Binary iterative hard thresholding converges with optimal number of measurements for 1-bit compressed sensing.Journal of the ACM, 71(5):1–64, 2024

Reference 32

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raw_fallback, observed 2026-08-07T14:42:17.869022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 316dc508-04aa-4413-b9e9-0860def23c90 · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Playing Atari with Deep Reinforcement Learning

Reference 33

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no resolver link, observed 2026-08-07T14:42:12.923457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:42:12.923457Z digest=sha256:2f2f623a4265a8d942911a1c40c786f6184cf31825081d1ab16f6991a580898e

Observation b753faab-4944-4ae4-b4e8-ac7dc70be64f · outbound

This paper cites Straight-Through meets Sparse Recovery: the Support Exploration Algorithm.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Straight-Through meets Sparse Recovery: the Support Exploration Algorithm

Reference 34

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verified exact
local_arxiv, observed 2026-08-07T14:42:15.261756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:12.977198Z digest=sha256:9caef0be0e98b4f7ed5242e485e2de466913abb2ad24de7928ea0636a8ff2c8b

Observation 07715636-85fc-4a84-a2de-75d54bd9d96a · outbound

This paper cites Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator

Reference 35

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no resolver link, observed 2026-08-07T14:42:13.065399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:42:13.065399Z digest=sha256:358f21c4c6eff81a6b10dc506e965d193f738f71b0a120aa4ba49714a9cbc728

Observation 57c118df-7810-4fc4-8e07-a746e31643b3 · outbound

This paper cites Cambridge university press, 1989.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Cambridge university press, 1989

Reference 36

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raw_fallback, observed 2026-08-07T14:42:17.673227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:13.128940Z digest=sha256:4822ae0e8a8e7a57aa94fa46ebb1282e10b6c5cedab84b0305dc6dd23a411584

Observation 67c88457-de6b-4d23-bc37-155674ea6581 · outbound

This paper cites Robust 1-bit compressed sensing and sparse logistic regression: A convex programming approach.IEEE Transactions on Information Theory, 59(1):482–494, 2012.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Robust 1-bit compressed sensing and sparse logistic regression: A convex programming approach.IEEE Transactions on Information Theory, 59(1):482–494, 2012

Reference 37

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no resolver link, observed 2026-08-07T14:42:13.221963Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:42:13.221963Z digest=sha256:5083555b0fcec4496dfde5b74f4a301226e4d5f3c840dc2d6c05e1329a2dda02

Observation c9ea3de6-eecf-454a-a91b-28b846c0beda · outbound

This paper cites One-bit compressed sensing by linear programming.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization One-bit compressed sensing by linear programming

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-07T14:42:17.522234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:13.317894Z digest=sha256:f7d2047fa896ed4b324e91d592b3a8d1839f4788e14a5304e34bc9473ecd010a

Observation 23e5ca4a-db96-41ba-9532-a5b9e3494553 · outbound

This paper cites The generalized lasso with non-linear observations.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization The generalized lasso with non-linear observations

Reference 39

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verified fuzzy
raw_fallback, observed 2026-08-07T14:42:17.395595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:13.412679Z digest=sha256:5b8dfc97f2221977b57ff2456dee8f876f0d60a31c184347a6d67082288f00fd

Observation bf8f6208-38b1-46e8-9d89-38d57e4a209b · outbound

This paper cites Xnor- net: Imagenet classification using binary convolutional neural networks.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Xnor- net: Imagenet classification using binary convolutional neural networks

Reference 40

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verified fuzzy
raw_fallback, observed 2026-08-07T14:42:17.205077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:13.468292Z digest=sha256:183cc61e2786be04b268a7217f8c9da7920c0cd430a20434bd6b3a5e547ab47c

Observation cc03d08f-c354-4472-b33b-2ee53bac41e1 · outbound

This paper cites Learning strides in convolutional neural networks.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Learning strides in convolutional neural networks

Reference 41

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verified exact
local_arxiv, observed 2026-08-07T14:42:15.142035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:13.568449Z digest=sha256:aada20c1a4f64818eec28e2c4ee078b86f497e307c7943a034739aae7d77dc31

Observation 713fec4e-4ba8-4815-a1b7-a29a4cc85238 · outbound

This paper cites Cornell Aeronautical Laboratory, 1957.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Cornell Aeronautical Laboratory, 1957

Reference 42

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raw_fallback, observed 2026-08-07T14:42:17.125662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:13.672965Z digest=sha256:149b45de301ef9df734f1b37fbed5168764c72d73ff9edb4b9d70a384b10b9ab

Observation c5da6ada-7b8f-403d-86b8-dea451530940 · outbound

This paper cites Spartan Book, 1962.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Spartan Book, 1962

Reference 43

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verified fuzzy
raw_fallback, observed 2026-08-07T14:42:17.055592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:13.744946Z digest=sha256:71e5a62fdea406fe1869fb8120b4e2b25ead82614975786f6264b24df6dbf94a

Observation 00a0b161-034b-4891-a481-4ee7fb509758 · outbound

This paper cites Neural network approximation: Three hidden layers are enough.Neural Networks, 141:160–173, 2021.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Neural network approximation: Three hidden layers are enough.Neural Networks, 141:160–173, 2021

Reference 44

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verified fuzzy
raw_fallback, observed 2026-08-07T14:42:16.960786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:13.810384Z digest=sha256:57ace4048f9546d345318e7e4c9ff2baa68fe09561f5dc7e4cca34c32f57b923

Observation 3086ac78-f5bf-4a66-8ed3-cccd54a87880 · outbound

This paper cites High-order approximation rates for shallow neural networks with cosine and reluk activation functions.Applied and Computational Harmonic Analysis, 58:1–26, 2022.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization High-order approximation rates for shallow neural networks with cosine and reluk activation functions.Applied and Computational Harmonic Analysis, 58:1–26, 2022

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:42:16.866957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:13.913252Z digest=sha256:fb74ffc3d64aba3f02b71ab82ec89847df70d69b6823df31bf237397af98bc00

Observation a6be7e33-67b6-4481-9178-a4d980198dd4 · outbound

This paper cites Single-path mobile automl: Efficient convnet design and nas hyperparameter optimization.IEEE Journal of Selected Topics in Signal Processing, 14(4):609–622, 2020.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Single-path mobile automl: Efficient convnet design and nas hyperparameter optimization.IEEE Journal of Selected Topics in Signal Processing, 14(4):609–622, 2020

Reference 46

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verified fuzzy
raw_fallback, observed 2026-08-07T14:42:16.758148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:14.001300Z digest=sha256:a880a96f8aca09d8b81bd956e4760cbca09afd0a89278484d851bda1cd30b7cd

Observation aa11221c-0766-48f0-96cb-ea6ae69f2154 · outbound

This paper cites Policy gradient methods for reinforcement learning with function approximation.Advances in neural information processing systems, 12, 1999.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Policy gradient methods for reinforcement learning with function approximation.Advances in neural information processing systems, 12, 1999

Reference 47

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no resolver link, observed 2026-08-07T14:42:14.047008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:42:14.047008Z digest=sha256:b5c6f22c00cd80ae86c466c8ca08df93bfde9a171e2e1f754c6fdeede3c9f8c0

Observation 0b3dd2a1-234d-437e-8c88-ed8129c1e6e5 · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 48

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no resolver link, observed 2026-08-07T14:42:14.111899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:42:14.111899Z digest=sha256:ddbff7f14de4e252db5c672da1a281bb6da2aaffb0b9e072db0940d00a64a9b5

Observation 7b8926ea-46b3-4585-93f7-5c31b38b6d47 · outbound

This paper cites Cambridge university press, 2018.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Cambridge university press, 2018

Reference 49

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no resolver link, observed 2026-08-07T14:42:14.219258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:42:14.219258Z digest=sha256:8213f7e107ed92c13d7063345d478bc0b13a7eb4ebf3a66daa05fd99cee3e332

Observation 375f52a6-7796-4886-b36d-5c4429f34b77 · outbound

This paper cites Memory capacity of neural networks with threshold and rectified linear unit activations.SIAM Journal on Mathematics of Data Science, 2(4):1004–1033, 2020.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Memory capacity of neural networks with threshold and rectified linear unit activations.SIAM Journal on Mathematics of Data Science, 2(4):1004–1033, 2020

Reference 50

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no resolver link, observed 2026-08-07T14:42:14.266339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:42:14.266339Z digest=sha256:bed069f117ff44444bb835666e252b0463c49535f51855e54872b8cced027de5

Observation 3f75f6c8-db2f-495f-99db-ab8ff23a51ec · outbound

This paper cites Universal approximation of functions on sets.Journal of Machine Learning Research, 23(151):1–56, 2022.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Universal approximation of functions on sets.Journal of Machine Learning Research, 23(151):1–56, 2022

Reference 51

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verified fuzzy
raw_fallback, observed 2026-08-07T14:42:16.650835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:14.344457Z digest=sha256:2b6031f06a903ef8d9b038766e923090fe80d1a8a84ebaf301f973be27cdd0af

Observation 25ae062c-4aff-4d28-8bdb-6e220ea41b48 · outbound

This paper cites Training deep neural networks with 8-bit floating point numbers.Advances in neural information processing systems, 31, 2018.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Training deep neural networks with 8-bit floating point numbers.Advances in neural information processing systems, 31, 2018

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:42:16.485003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:14.397156Z digest=sha256:dd049b8e3ac0775f5afa20e973e7094bb3839e007cf46bdd52e6c70d21629d99

Observation af633ce9-fa78-45fe-9e8d-52d6ada65d07 · outbound

This paper cites RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models

Reference 53

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no resolver link, observed 2026-08-07T14:42:14.467357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:42:14.467357Z digest=sha256:01acbe17149c2d23c264281a3a8054e3a61372ad6460dbda65e510452e852884

Observation 7b8ae617-d2ad-4d38-aec2-d6dd4f9b438f · outbound

This paper cites Relation embedding with dihedral group in knowledge graph.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Relation embedding with dihedral group in knowledge graph

Reference 54

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verified fuzzy
raw_fallback, observed 2026-08-07T14:42:16.323210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:14.526825Z digest=sha256:a17853c87267ed3fb1de0b2bfe34cd783715e848cc8cff909b090c1c87319234

Observation d2585ddf-288f-406a-9153-97f4ccfc95be · outbound

This paper cites Injecting logical constraints into neural networks via straight-through estimators.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Injecting logical constraints into neural networks via straight-through estimators

Reference 55

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verified fuzzy
raw_fallback, observed 2026-08-07T14:42:16.166125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:14.604226Z digest=sha256:810d598850ab5d0121a2d10eb764039da4c706af82721b2b4758c7ceaa65f5aa

Observation f1c41f82-b792-4386-839b-b998a8a88e28 · outbound

This paper cites Ratio and difference ofl1 and l2 norms and sparse representation with coherent dictionaries.Commun.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Ratio and difference ofl1 and l2 norms and sparse representation with coherent dictionaries.Commun

Reference 56

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verified fuzzy
raw_fallback, observed 2026-08-07T14:42:16.034953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:14.659876Z digest=sha256:2b1df75b7502363444c6c4a163d09f186578c79cf9700cdba6bcfe9b21e96a50

Observation 5bd3972b-03c6-42bb-90b4-be271532f80e · outbound

This paper cites Understanding straight-through estimator in training activation quantized neural nets.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Understanding straight-through estimator in training activation quantized neural nets

Reference 57

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unresolved
no resolver link, observed 2026-08-07T14:42:14.716599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:42:14.716599Z digest=sha256:4dfec669e03f958ebbde47d21567b1e288b53f3a8853366cd261e22ce4afbf9a

Observation 65acbe60-8f04-49a1-8df5-8e69e0f03012 · outbound

This paper cites Binaryrelax: A relaxation approach for training deep neural networks with quantized weights.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Binaryrelax: A relaxation approach for training deep neural networks with quantized weights

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:42:15.975254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:14.770410Z digest=sha256:381351b32921bbc6aacc11ab446831e77a9b8ad623779c5f8d3857f05a0d2d4f

Observation 8867620f-f48d-439e-b433-7144ff54375d · outbound

This paper cites Blended coarse gradient descent for full quantization of deep neural networks.Research in the Mathematical Sciences, 6(1), 2019.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Blended coarse gradient descent for full quantization of deep neural networks.Research in the Mathematical Sciences, 6(1), 2019

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:42:15.871103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:14.802798Z digest=sha256:ff61404a0857f75e1d46f21cbb987b9669256c6c7ded81e990781273726e747e

Observation 606a7459-f2df-459d-8979-ba75cbe8653d · outbound

This paper cites correct" sign region within one time step of entering the “incorrect.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization correct" sign region within one time step of entering the “incorrect

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:42:15.777625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:14.867542Z digest=sha256:61ac301831e43dc50a079e177fbcb563998cddcdc62106c6dd3a81a5077815e2

Observation a0a7bd61-874b-4967-b8dd-5c16eb1e6dac · outbound

This paper cites an unresolved cited work.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization Unresolved cited work

Reference 61

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:42:15.705133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:14.910494Z digest=sha256:e260ca46df50b75ee278341e01b0d3ab790afe7acfd309e14f5c24b415b1ac6c

Observation abab3d69-c6e1-4de8-b677-95eaa05b87a8 · outbound

This paper cites This also impiles thatP (G ̸= 0) = 1.

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization This also impiles thatP (G ̸= 0) = 1

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:42:15.574434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:42:14.965641Z digest=sha256:10ad1415412ad02b9c3f63b57e5b7abd0e843cd72d252cff40fb72124edc6159

Pith citing papers

Observation ec78f4be-1fc0-4e6f-b309-639bdde9dcf9 · inbound

Training Non-Differentiable Networks via Optimal Transport cites this paper.

Training Non-Differentiable Networks via Optimal Transport Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization

Reference 59

Resolution
verified exact
arxiv_id, observed 2026-06-02T04:04:23.627629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T15:37:42.167420Z digest=sha256:066323ace1b5f9ccd30804a6820f942d2a5512ebec7d442a05e378ec8cc23a70

Observation 4f4bbd0f-94ce-496b-8e62-cac17f117fef · inbound

Understanding Quantization-Aware Training: Gradients at Quantized Weights Bias to the Low-Loss Basin cites this paper.

Understanding Quantization-Aware Training: Gradients at Quantized Weights Bias to the Low-Loss Basin Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-07-02T23:57:29.100941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T17:34:20.870403Z digest=sha256:38fb79cce9788123f256a6a3200f15f6c417f49b328d9c2f875b646c837c5d01