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Paper Citation Record · LEDGER

Layer-wise Quantization for Quantized Optimistic Dual Averaging

As of 9 August 2026, this Paper Citation Record lists 100 of 101 outbound references and 0 inbound Pith citation observations for arXiv:2505.14371.

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

pith.paper-citation-record.v1
2505.14371 v1

Coverage vector

measured 100 of 101 reference resolution

Typed states for the displayed outbound observations.

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measured 100 of 100 standing notices

One-hop event checks from named stored sources.

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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 101 outbound references displayed

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  • verified fuzzy48
  • unresolved45
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External citation measurements

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Outbound references

Observation 99af8598-f2c6-4600-b70a-86a4dab376bb · outbound

This paper cites write newline.

Layer-wise Quantization for Quantized Optimistic Dual Averaging write newline

Reference 1

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source=arxiv_source observed=2026-08-07T15:43:01.910819Z digest=sha256:780403cd0bc058ccb5d41c50bb1560a90fa04226829b70babc952b9294a521cc

Observation e2990d4d-069e-46c6-be57-ab9572b3f385 · outbound

This paper cites https://developer.nvidia.com/nccl, 2023.

Layer-wise Quantization for Quantized Optimistic Dual Averaging https://developer.nvidia.com/nccl, 2023

Reference 2

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Observation dae022bb-9370-4fa2-aae6-d41d5a95a416 · outbound

This paper cites https://www.open-mpi.org/, 2023.

Layer-wise Quantization for Quantized Optimistic Dual Averaging https://www.open-mpi.org/, 2023

Reference 3

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Observation 10e4eb10-889c-4764-bbf2-f3c782b1d7a6 · outbound

This paper cites Adaptive gradient communication via critical learning regime identification.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Adaptive gradient communication via critical learning regime identification

Reference 4

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Observation b8974dd5-fec8-4e56-9ddd-57f8114a4a81 · outbound

This paper cites QSGD : Communication-efficient SGD via gradient quantization and encoding.

Layer-wise Quantization for Quantized Optimistic Dual Averaging QSGD : Communication-efficient SGD via gradient quantization and encoding

Reference 5

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Observation 77bf7afe-6429-4bdb-a631-245e215af6e2 · outbound

This paper cites An adaptive mirror-prox method for variational inequalities with singular operators.

Layer-wise Quantization for Quantized Optimistic Dual Averaging An adaptive mirror-prox method for variational inequalities with singular operators

Reference 6

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This paper cites Sifting through the noise: Universal first-order methods for stochastic variational inequalities.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Sifting through the noise: Universal first-order methods for stochastic variational inequalities

Reference 7

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Observation 885b981a-d659-490a-a47a-11868a3604eb · outbound

This paper cites Wasserstein generative adversarial networks.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Wasserstein generative adversarial networks

Reference 8

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Observation 8ee2f8ee-5d9a-4f9b-81fb-163df8b26359 · outbound

This paper cites EfQAT: An Efficient Framework for Quantization-Aware Training.

Layer-wise Quantization for Quantized Optimistic Dual Averaging EfQAT: An Efficient Framework for Quantization-Aware Training

Reference 9

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Observation f629568b-0a79-44a6-9419-a7df04870ba7 · outbound

This paper cites Adaptive and self-confident on-line learning algorithms.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Adaptive and self-confident on-line learning algorithms

Reference 10

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Layer-wise Quantization for Quantized Optimistic Dual Averaging and Levy, K

Reference 11

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 12

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Observation bab555b6-5250-474a-a240-5cebd36c3eb9 · outbound

This paper cites Distributed methods with compressed communication for solving variational inequalities, with theoretical guarantees.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Distributed methods with compressed communication for solving variational inequalities, with theoretical guarantees

Reference 13

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This paper cites Bregman proximal method for efficient communications under similarity, 2023 a.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Bregman proximal method for efficient communications under similarity, 2023 a

Reference 14

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Stochastic gradient descent-ascent: Unified theory and new efficient methods

Reference 15

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Layer-wise Quantization for Quantized Optimistic Dual Averaging and Pock, T

Reference 16

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This paper cites Reducing noise in gan training with variance reduced extragradient.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Reducing noise in gan training with variance reduced extragradient

Reference 17

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Online optimization with gradual variations

Reference 18

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 19

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Layer-wise Quantization for Quantized Optimistic Dual Averaging and Shanbhag, U

Reference 20

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Training GANs with Optimism

Reference 21

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Training GANs with optimism

Reference 22

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Layer-wise Quantization for Quantized Optimistic Dual Averaging New bounds for distributed mean estimation and variance reduction

Reference 23

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Layer-wise Quantization for Quantized Optimistic Dual Averaging S., Monga, R., Chen, K., Devin, M., Mao, M

Reference 24

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Layer-wise Quantization for Quantized Optimistic Dual Averaging An image is worth 16x16 words: Transformers for image recognition at scale

Reference 25

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Adaptive subgradient methods for online learning and stochastic optimization

Reference 26

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Layer-wise Quantization for Quantized Optimistic Dual Averaging H., Abdelmoniem, A

Reference 27

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Universal codeword sets and representations of the integers

Reference 28

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Layer-wise Quantization for Quantized Optimistic Dual Averaging and Le Nguyen, H

Reference 29

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Layer-wise Quantization for Quantized Optimistic Dual Averaging and Pang, J.-S

Reference 30

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Layer-wise Quantization for Quantized Optimistic Dual Averaging M., and Ramezani-Kebrya, A

Reference 31

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Layer-wise Quantization for Quantized Optimistic Dual Averaging OPTQ : Accurate quantization for generative pre-trained transformers

Reference 32

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Layer-wise Quantization for Quantized Optimistic Dual Averaging A Variational Inequality Perspective on Generative Adversarial Networks

Reference 33

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Layer-wise Quantization for Quantized Optimistic Dual Averaging A variational inequality perspective on generative adversarial networks

Reference 34

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Generative adversarial nets

Reference 35

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Accelerating distributed deep learning by adaptive gradient quantization

Reference 36

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Deep residual learning for image recognition

Reference 37

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Observation d4bc6531-3bf1-48ca-872c-2ecca1e79c73 · outbound

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Stochastic distributed learning with gradient quantization and double-variance reduction

Reference 38

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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.

source=arxiv_source observed=2026-08-07T15:43:06.057259Z digest=sha256:8aba8930f0f93cb0cf6ffa66c3aceb931f14ab170bfb5617e97dfd4c53b6d110

Observation 6d113eca-06d9-4b46-874e-68e20aa9341c · outbound

This paper cites Explore aggressively, update conservatively: Stochastic extragradient methods with variable stepsize scaling.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Explore aggressively, update conservatively: Stochastic extragradient methods with variable stepsize scaling

Reference 39

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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.

source=arxiv_source observed=2026-08-07T15:43:06.239863Z digest=sha256:07b99e7b572e43fd70f5bbbc86574abc791179a7a1d602fdd21fac626f2c845f

Observation e29dde7d-89b6-4a8d-bc43-ec072809397b · outbound

This paper cites Adaptive learning in continuous games: Optimal regret bounds and convergence to nash equilibrium.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Adaptive learning in continuous games: Optimal regret bounds and convergence to nash equilibrium

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:30.350292Z

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=2026-08-07T15:43:06.341198Z digest=sha256:cc0372d9e2f647676744e90f5bc3c67c10b5ef2ed4bd5aeba8f324e8728339d2

Observation f1bf06d3-0675-4bf5-9b3e-d29cd3117649 · outbound

This paper cites No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation.

Layer-wise Quantization for Quantized Optimistic Dual Averaging No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation

Reference 41

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verified fuzzy
raw_fallback, observed 2026-08-07T15:43:27.046442Z

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=2026-08-07T15:43:06.550626Z digest=sha256:cbfb5fbbd012da04053e763de43d02ba97404ed05d57c616b364d2d14340df7e

Observation b0949b2b-5af3-4fbb-817a-ae0df3746771 · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 42

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no resolver link, observed 2026-08-07T15:43:06.726274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:43:06.726274Z digest=sha256:f63df19ab5ea6b9c10595067bcde6959fef7ce7698375fb898e3eac6bc6d0bd0

Observation d89be226-4937-4841-854a-cdf97a977294 · outbound

This paper cites N., Jofr \'e , A., Oliveira, R.

Layer-wise Quantization for Quantized Optimistic Dual Averaging N., Jofr \'e , A., Oliveira, R

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:25.851144Z

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=2026-08-07T15:43:06.863506Z digest=sha256:6273dd772598e82f7e1cc3769163fa5aaee3e5a12e299ad3b19cfdb8b47c644a

Observation 72a685f9-10e7-4029-8005-3d74f7440150 · outbound

This paper cites and Sidford, A.

Layer-wise Quantization for Quantized Optimistic Dual Averaging and Sidford, A

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:25.623104Z

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=2026-08-07T15:43:06.983131Z digest=sha256:5b486d8abea116acee69abb1fb17e262e34c33c800a60b7192fa57839d280da9

Observation 70701d06-933e-43a9-90ad-7cfd1235b017 · outbound

This paper cites Solving variational inequalities with stochastic mirror-prox algorithm.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Solving variational inequalities with stochastic mirror-prox algorithm

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:25.393669Z

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=2026-08-07T15:43:07.126876Z digest=sha256:55f6bb90930e55bbc2f14c0d1fabf439a9f5cf08201ac3b0d378b19ab9f1a3a8

Observation 92d09cd2-2ee9-48f3-88b7-452282b0a702 · outbound

This paper cites B., Avent, B., Bellet, A., Bennis, M., Bhagoji, A.

Layer-wise Quantization for Quantized Optimistic Dual Averaging B., Avent, B., Bellet, A., Bennis, M., Bhagoji, A

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:25.043889Z

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=2026-08-07T15:43:07.279900Z digest=sha256:68c0bf80d1dade6f66fb4198826b3957aab522fc3ba5ffc805ac5cb1147f5ea8

Observation 6930d33c-9765-46ec-a45e-751c872521af · outbound

This paper cites Robust reinforcement learning via adversarial training with langevin dynamics.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Robust reinforcement learning via adversarial training with langevin dynamics

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:24.775001Z

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=2026-08-07T15:43:07.397791Z digest=sha256:483cde4e21e32c33b7dea13c23187e79e44666ed7043f7fb7e4f5de612316fb9

Observation 7f874994-1d51-4b40-aeaf-90cad10fcd8d · outbound

This paper cites and Shanbhag, U.

Layer-wise Quantization for Quantized Optimistic Dual Averaging and Shanbhag, U

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:24.563687Z

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=2026-08-07T15:43:07.555378Z digest=sha256:fc781bf3d0efd8e6a8be34e502670d200c72e9ec11f419d0030f31e2e0c2b464

Observation 173570c5-310d-4d8a-9b9b-91d7abd5bd22 · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-07T15:43:24.095079Z

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=2026-08-07T15:43:07.652661Z digest=sha256:a640d081be0c1e4c2170cfc57ca7642b759d86e75e206152ec9faba0155273c8

Observation 5a8868cb-6a96-4665-97c2-598fbe382eda · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T15:43:07.765577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:43:07.765577Z digest=sha256:a76e197a461ea5f911e2fc087ab30e5a981efc5a53049473804496d131b8318f

Observation f2ae1acc-3078-4140-a492-790d5f35db1c · outbound

This paper cites Optimal algorithms for decentralized stochastic variational inequalities.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Optimal algorithms for decentralized stochastic variational inequalities

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:23.764482Z

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=2026-08-07T15:43:07.858372Z digest=sha256:1af5a0ba769dee93a67ce1280cdfcdb1e7358d093df240f15874364faa6c2389

Observation 89eb0717-5671-4c99-b8e4-febb2b1f1df7 · outbound

This paper cites Learning multiple layers of features from tiny images.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Learning multiple layers of features from tiny images

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T15:43:07.990694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:43:07.990694Z digest=sha256:0844752d563ab5ea14ca44bf840ec4f006b332468cb444c3f0a7e1d10d498023

Observation 27d98848-0d24-403a-bfbc-184e69e22fc2 · outbound

This paper cites Y., Yurtsever, A., and Cevher, V.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Y., Yurtsever, A., and Cevher, V

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:23.528593Z

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=2026-08-07T15:43:08.065270Z digest=sha256:a6d6ae828740c6a6c2d7c6074de2033da51d2445f04a719c019acfac6a1f8a72

Observation 84640e9d-f05b-41f9-93f0-6c5c208256a6 · outbound

This paper cites Det-cgd: Compressed gradient descent with matrix stepsizes for non-convex optimization.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Det-cgd: Compressed gradient descent with matrix stepsizes for non-convex optimization

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:23.315228Z

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=2026-08-07T15:43:08.197476Z digest=sha256:5deb0f846c5714316cf1e7232320fb22f186076cae17082a29b9c6b813ac62e0

Observation 817b80e0-5392-4d44-a328-dd2dfcd2200e · outbound

This paper cites K., Talwalkar, A., and Smith, V.

Layer-wise Quantization for Quantized Optimistic Dual Averaging K., Talwalkar, A., and Smith, V

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T15:43:08.298615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:43:08.298615Z digest=sha256:20726caefe4033955c345e4e2712729f485d5c98821110dfd20c7c697432c829

Observation c8ef3562-1486-42ae-be43-7df71c3a1b24 · outbound

This paper cites Finite-time last-iterate convergence for multi-agent learning in games.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Finite-time last-iterate convergence for multi-agent learning in games

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:23.122366Z

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=2026-08-07T15:43:08.447558Z digest=sha256:c5188b5974441ab82d2328717082c7b3c26191be5ba04e51073f7d78a65dc61e

Observation 679d918a-0fc5-45d8-ba28-2dcb482b61e4 · outbound

This paper cites Adaptive Compression for Communication-Efficient Distributed Training.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Adaptive Compression for Communication-Efficient Distributed Training

Reference 57

Resolution
verified exact
local_arxiv, observed 2026-08-07T15:43:15.018902Z

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=2026-08-07T15:43:08.529344Z digest=sha256:09627728978f2c9d6a4a22d03a0c73020434272597882a7b4ddd89cd39a51e89

Observation ec6a53ad-7b0c-4676-8a4a-07059ef52b4e · outbound

This paper cites Projected reflected gradient methods for monotone variational inequalities.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Projected reflected gradient methods for monotone variational inequalities

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:22.934854Z

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=2026-08-07T15:43:08.637605Z digest=sha256:15505a4c83008974da4710ae7ae19b4345c385a107bb613058eca059379ae2a8

Observation bd7781e7-f631-40fb-bd57-edaf8f296bb9 · outbound

This paper cites Golden ratio algorithms for variational inequalities.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Golden ratio algorithms for variational inequalities

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:22.703758Z

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=2026-08-07T15:43:08.727760Z digest=sha256:d955cab5b5acd37d45b5a6310b731488d91d1c5cbc94e0c8c4ab9520a8c4213d

Observation 86288cc2-73b2-4829-bfa1-64b4e1f7d790 · outbound

This paper cites Cgx: adaptive system support for communication-efficient deep learning.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Cgx: adaptive system support for communication-efficient deep learning

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:22.530413Z

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=2026-08-07T15:43:08.823460Z digest=sha256:cb1e494655a62d6e1fc054f6f0cbd85268bf26d85c09024b179406c75f4a59e5

Observation 9b0335c0-f150-449b-bdd8-7b00667940ad · outbound

This paper cites L-greco: Layerwise-adaptive gradient compression for efficient data-parallel deep learning.

Layer-wise Quantization for Quantized Optimistic Dual Averaging L-greco: Layerwise-adaptive gradient compression for efficient data-parallel deep learning

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:22.312236Z

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=2026-08-07T15:43:08.964833Z digest=sha256:de31dd95be3ffe879dd94568a703bc3ec01160f7f71f10cb0069dadd3802ae4c

Observation dfe37ab8-21dc-4dba-91e4-ed849a7ba4cc · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 62

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unresolved
no resolver link, observed 2026-08-07T15:43:09.115269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:43:09.115269Z digest=sha256:2ab5976b44575d175b7a34ddcfd1947f8ef2eb19750e28d3f747af561bebcf3b

Observation ac5b9f13-810a-460d-ab42-e95ee75c071f · outbound

This paper cites Adaptive Bound Optimization for Online Convex Optimization.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Adaptive Bound Optimization for Online Convex Optimization

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-07T15:43:09.208938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:43:09.208938Z digest=sha256:af6154547ad5410752bf24a83399b3b714eabd38be09a8ed60150581027aa527

Observation 563fac6f-470a-49ad-ac05-2764683bcd32 · outbound

This paper cites Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-07T15:43:09.283738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:43:09.283738Z digest=sha256:09b7b4f18980f92310805208ad2eeb0dfe9ba13c30d31493fc66f02d087b4b66

Observation 03a86cd5-4450-4b8d-9527-b4e3b52e859c · outbound

This paper cites Intsgd: Adaptive floatless compression of stochastic gradients.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Intsgd: Adaptive floatless compression of stochastic gradients

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:22.044751Z

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=2026-08-07T15:43:09.411499Z digest=sha256:bfa8d9c26cf32cd74487a61ca11a7fc50b82694036355bd0ed4ab18b9c1886ce

Observation 8396f1ff-a0d8-4ea3-a9b4-2b32175b678d · outbound

This paper cites Distributed learning with compressed gradient differences.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Distributed learning with compressed gradient differences

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:21.903346Z

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=2026-08-07T15:43:09.534796Z digest=sha256:156af317570b80f8afb0a3da84b2a96347fa9df9bbdb16a7971d9f7131ea742f

Observation d8b6a7ac-b63d-4eec-8530-e3ded17bd7a5 · outbound

This paper cites A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach.

Layer-wise Quantization for Quantized Optimistic Dual Averaging A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach

Reference 67

Resolution
verified exact
local_arxiv, observed 2026-08-07T15:43:14.822487Z

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=2026-08-07T15:43:09.714739Z digest=sha256:bb02ff5f41458ea534f5f543cf9754b29ff4474880a1d3c95be9d85759f355e1

Observation b8b69285-041e-4f06-b101-ad7e7d7aee2d · outbound

This paper cites Convergence Rate of $\mathcal{O}(1/k)$ for Optimistic Gradient and Extra-gradient Methods in Smooth Convex-Concave Saddle Point Problems.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Convergence Rate of $\mathcal{O}(1/k)$ for Optimistic Gradient and Extra-gradient Methods in Smooth Convex-Concave Saddle Point Problems

Reference 68

Resolution
verified exact
local_arxiv, observed 2026-08-07T15:43:14.596502Z

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=2026-08-07T15:43:09.797622Z digest=sha256:88915f669d471865166ee47eafc07fb4ba75dde9c1f2e12a6cf3e7137f560636

Observation f874265f-2a4f-4b40-a9af-65d09ce3d5fa · outbound

This paper cites Prox-method with rate of convergence o(1/t) for variational inequalities with lipschitz continuous monotone operators and smooth convex-concave saddle point problems.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Prox-method with rate of convergence o(1/t) for variational inequalities with lipschitz continuous monotone operators and smooth convex-concave saddle point problems

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:21.650281Z

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=2026-08-07T15:43:09.891634Z digest=sha256:9469d52481e99e971eff9878dd210a0b6705d45c542d724e81aada1e1867e440

Observation a6cafcba-d9a3-4548-8794-478514bfbf45 · outbound

This paper cites Robust stochastic approximation approach to stochastic programming.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Robust stochastic approximation approach to stochastic programming

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-07T15:43:10.002753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:43:10.002753Z digest=sha256:6330ef7661e081e29b23d79529ff14e46dc9272fe2c2300d4db403f36eb0fadf

Observation 718f3028-35ad-46b8-8f6f-616af40f320f · outbound

This paper cites Introductory Lectures on Convex Optimization: A Basic Course.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Introductory Lectures on Convex Optimization: A Basic Course

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:21.403892Z

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=2026-08-07T15:43:10.079913Z digest=sha256:29f5dcc43d9a39b3309943e5b744dee67be28f95bdea9543a303be93d11501a2

Observation be174f62-2a91-4269-917b-69e3dec80519 · outbound

This paper cites Dual extrapolation and its applications to solving variational inequalities and related problems.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Dual extrapolation and its applications to solving variational inequalities and related problems

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:21.176062Z

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=2026-08-07T15:43:10.173067Z digest=sha256:148dde7e599e75fda0ddf4feac8318fc52ed16f65bf5b7dc673b1d4c3f798a05

Observation 64937844-11c0-4cc3-8ed6-704897adbd53 · outbound

This paper cites Primal-dual subgradient methods for convex problems.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Primal-dual subgradient methods for convex problems

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:20.933831Z

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=2026-08-07T15:43:10.306518Z digest=sha256:b7686e98051f0ae2818d3f903f665645fb30bfaa0878600ead06de0dca308631

Observation 4ed56d01-4117-4f51-8b05-abeb8660b244 · outbound

This paper cites P., and Vian, J.

Layer-wise Quantization for Quantized Optimistic Dual Averaging P., and Vian, J

Reference 74

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verified fuzzy
raw_fallback, observed 2026-08-07T15:43:20.676144Z

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=2026-08-07T15:43:10.407705Z digest=sha256:fc7fcb857c5b1c8401d8744882af25a40dcfae751597e175ff71a81373f19aaa

Observation ee935c71-e16f-44e0-9170-956515b9529b · outbound

This paper cites and Soltanolkotabi, M.

Layer-wise Quantization for Quantized Optimistic Dual Averaging and Soltanolkotabi, M

Reference 75

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no resolver link, observed 2026-08-07T15:43:10.574048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6c37b09d-373c-4f86-86ef-53eee291e73c · outbound

This paper cites Training GANs with Centripetal Acceleration.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Training GANs with Centripetal Acceleration

Reference 76

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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 2026-08-09T06:31:02.800959+00:00.

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Observation ac913823-8ccc-402e-b701-4b80d8eef385 · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 77

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raw_fallback, observed 2026-08-07T15:43:20.465765Z

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=2026-08-07T15:43:10.834473Z digest=sha256:f4cdd32e989a11eda3842b2935a3d35f2f3be7db02eff44a6ae0b2ab92ec093d

Observation 622ea920-5af3-41f8-92a3-f8e2bfa301ef · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 78

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raw_fallback, observed 2026-08-07T15:43:20.154546Z

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 9207e963-4c25-4189-be86-c0a7a07670e0 · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 79

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raw_fallback, observed 2026-08-07T15:43:19.888901Z

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 e63ac9d0-ec28-4c84-9dfb-27e02831a853 · outbound

This paper cites Mixtailor: Mixed gradient aggregation for robust learning against tailored attacks.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Mixtailor: Mixed gradient aggregation for robust learning against tailored attacks

Reference 80

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verified fuzzy
raw_fallback, observed 2026-08-07T15:43:19.654986Z

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 7c3bc914-4d3c-4b61-af4c-2f131eb7ec56 · outbound

This paper cites Distributed extra-gradient with optimal complexity and communication guarantees.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Distributed extra-gradient with optimal complexity and communication guarantees

Reference 81

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verified fuzzy
raw_fallback, observed 2026-08-07T15:43:19.367968Z

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=2026-08-07T15:43:11.377916Z digest=sha256:e35d5ba24dd6343897bb3a2a59d00b723eeac4ca95b9b420b5448cf8d5bcc067

Observation 61a4f09c-e666-4da6-b747-76f7801ea6fa · outbound

This paper cites Adversarially robust generalization requires more data.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Adversarially robust generalization requires more data

Reference 82

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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.

source=arxiv_source observed=2026-08-07T15:43:11.496246Z digest=sha256:a06a4e67fa41c13e51191530e030eb9fb28ed994f4f5ba2632b44f7eed1880fc

Observation 30847bc3-2da2-493d-ad5f-476810a26007 · outbound

This paper cites Scalable distributed DNN training using commodity GPU cloud computing.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Scalable distributed DNN training using commodity GPU cloud computing

Reference 83

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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.

source=arxiv_source observed=2026-08-07T15:43:11.598185Z digest=sha256:13c453eb60bc5decb93325ed3305fbc06680389afcb87ca7694e6dfdc4382297

Observation 0a73608f-6dcd-44b2-be56-50ba7315f390 · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 84

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unresolved
raw_fallback, observed 2026-08-07T15:43:18.632188Z

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 37aa223e-64f9-4bdd-8eee-65ae1bbc0c4f · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 85

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unresolved
raw_fallback, observed 2026-08-07T15:43:18.403526Z

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 ff5fbdd6-bf07-4887-8d2d-ae476ac35091 · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 86

Resolution
unresolved
raw_fallback, observed 2026-08-07T15:43:18.182723Z

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 71010c99-57e4-434d-b844-f4db42d91522 · outbound

This paper cites J., Wu, Y., Takac, M., Nandakumar, K., Horv \'a th, S., and Gorbunov, E.

Layer-wise Quantization for Quantized Optimistic Dual Averaging J., Wu, Y., Takac, M., Nandakumar, K., Horv \'a th, S., and Gorbunov, E

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:17.976108Z

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=2026-08-07T15:43:12.134309Z digest=sha256:4973d869738bd152e5044f3123dcf5ce58cb4666fd61efee36d92697dd205e01

Observation 76988e9f-92f5-435e-86e6-eb7b0cea34e1 · outbound

This paper cites N., Kaiser, ., and Polosukhin, I.

Layer-wise Quantization for Quantized Optimistic Dual Averaging N., Kaiser, ., and Polosukhin, I

Reference 88

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verified fuzzy
raw_fallback, observed 2026-08-07T15:43:17.777565Z

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=2026-08-07T15:43:12.217688Z digest=sha256:db3a81fe4f96a1d0e9c1483850cdc7159a6add717f3f5fd270cb7c6ddd56aa29

Observation d9f84d80-1e66-4e50-9ce7-fafbabcb4d22 · outbound

This paper cites Delay jitter control for real-time communication in a packet switching network.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Delay jitter control for real-time communication in a packet switching network

Reference 89

Resolution
metadata mismatch
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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.

source=arxiv_source observed=2026-08-07T15:43:12.347533Z digest=sha256:5918589abb2cba9e65c5c5dbb2c9828ee7fea91924322e8051c5e8c4660f2a04

Observation 4a0b54fc-c5c3-4e5d-8f47-bcf18ac3611a · outbound

This paper cites Theoretically better and numerically faster distributed optimization with smoothness-aware quantization techniques.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Theoretically better and numerically faster distributed optimization with smoothness-aware quantization techniques

Reference 90

Resolution
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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.

source=arxiv_source observed=2026-08-07T15:43:12.466923Z digest=sha256:532b241991f371e47f8731708055719a87b251cb1b150dc6d353a1892194ec90

Observation cca203ec-4551-4432-a41b-b23067525c50 · outbound

This paper cites Atomo: Communication-efficient learning via atomic sparsification.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Atomo: Communication-efficient learning via atomic sparsification

Reference 91

Resolution
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.

source=arxiv_source observed=2026-08-07T15:43:12.574647Z digest=sha256:c8320472a54ca2c339ce3af7a546f54c817f53b6d3a2907e5fc9a3c6ca324729

Observation ea5e5166-b618-4891-af95-36d9e5da89a9 · outbound

This paper cites TernGrad : Ternary gradients to reduce communication in distributed deep learning.

Layer-wise Quantization for Quantized Optimistic Dual Averaging TernGrad : Ternary gradients to reduce communication in distributed deep learning

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:17.025567Z

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=2026-08-07T15:43:12.670158Z digest=sha256:23e72921cbac896f8ff947191708c7bb2eee15f6247c461a0b89a1ab5db24750

Observation eb5de229-bfdf-4a4d-8ea9-33112ddd8d17 · outbound

This paper cites E., Bullins, B., Shamir, O., and Srebro, N.

Layer-wise Quantization for Quantized Optimistic Dual Averaging E., Bullins, B., Shamir, O., and Srebro, N

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:16.707106Z

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=2026-08-07T15:43:12.773203Z digest=sha256:d50b1fef59de5cfef0b1cbb39cdfa4c8ba2280765f1a10f146dddd0a5ba398ef

Observation 7c723383-0876-4df6-84d5-89e3f876f678 · outbound

This paper cites Mixed nash for robust federated learning.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Mixed nash for robust federated learning

Reference 94

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raw_fallback, observed 2026-08-07T15:43:16.478937Z

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=2026-08-07T15:43:12.826677Z digest=sha256:4b9284824ad5e6006c1fa355a17cf8e9b5ca097d41ffaebf7ad1506718efc3ba

Observation d2c99ca3-953c-499c-a075-de948e352c1a · outbound

This paper cites Kimad: Adaptive gradient compression with bandwidth awareness.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Kimad: Adaptive gradient compression with bandwidth awareness

Reference 95

Resolution
metadata mismatch
raw_fallback, observed 2026-08-07T15:43:13.718731Z

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=2026-08-07T15:43:12.910056Z digest=sha256:b1be70a041718cc463805947f96a0dec371b273855a903df4a1cd0f9a57a4f35

Observation 7e2eb9d5-bf51-4950-bce0-d761299755a5 · outbound

This paper cites Block-Normalized Gradient Method: An Empirical Study for Training Deep Neural Network.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Block-Normalized Gradient Method: An Empirical Study for Training Deep Neural Network

Reference 96

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unresolved
no resolver link, observed 2026-08-07T15:43:12.951097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:43:12.951097Z digest=sha256:efbeb35327ad2fceb5a63a5a96012b6c4b0ef5174bbe046f648c2a769b7e6249

Observation 5f045445-e606-4512-bc09-5b4ba8b90d4d · outbound

This paper cites Distributed dual averaging method for multi-agent optimization with quantized communication.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Distributed dual averaging method for multi-agent optimization with quantized communication

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:16.276048Z

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=2026-08-07T15:43:13.052843Z digest=sha256:6378096acf5944422f92d5b17c02de8cbf46ecb04b0f8bea16780e919b2e1953

Observation 2ac9c2f7-17dc-41c8-833d-6bdfc4f3f85a · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 98

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unresolved
no resolver link, observed 2026-08-07T15:43:13.145080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:43:13.145080Z digest=sha256:8c10915c264b19e7a259633e4678540cfe7381da5c606b68342378f4bdb28912

Observation 18fa1f5b-c047-4bf3-b6d0-db2b1393db3c · outbound

This paper cites Understanding deep learning (still) requires rethinking generalization.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Understanding deep learning (still) requires rethinking generalization

Reference 99

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no resolver link, observed 2026-08-07T15:43:13.226800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:43:13.226800Z digest=sha256:4679a4ffb64dfce80350175aa3354bf56ebe82817f4611dd9e8396d3036f8ece

Observation b777c825-a9e3-49bc-911c-fa53e21f9b12 · outbound

This paper cites ZipML : Training linear models with end-to-end low precision, and a little bit of deep learning.

Layer-wise Quantization for Quantized Optimistic Dual Averaging ZipML : Training linear models with end-to-end low precision, and a little bit of deep learning

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:43:16.069577Z

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=2026-08-07T15:43:13.296512Z digest=sha256:41738151cd1a04aaf0a49c1141356ebaf237439eaeff59b0daf4c0a9a5b351d8

Pith citing papers

No inbound Pith citation observations are available.