Paper Citation Record · LEDGER

A Unified Analysis for Finite Weight Averaging

As of 18 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 1 inbound Pith citation observation for arXiv:2411.13169.

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

pith.paper-citation-record.v1
2411.13169 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T16:54:00.648915Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T19:24:43.382361Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T19:24:43.477010Z

Reference resolution

45 of 45 outbound references displayed

verified exact0
verified fuzzy23
unresolved22
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 109aef07-71c0-4d89-91bc-792eb70d3bb0 · outbound

This paper cites Rademacher and gaussian complexities: Risk bounds and structural results.

A Unified Analysis for Finite Weight Averaging Rademacher and gaussian complexities: Risk bounds and structural results

Reference 1

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Source-reported events for the cited work

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Observation b096f6a8-59d0-4c8d-8633-823e91b65391 · outbound

This paper cites an unresolved cited work.

A Unified Analysis for Finite Weight Averaging Unresolved cited work

Reference 2

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Source-reported events for the cited work

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Observation 7faf82cd-9e96-46fa-874d-0ca6a465bd7f · outbound

This paper cites Learnability and the vapnik-chervonenkis dimension.

A Unified Analysis for Finite Weight Averaging Learnability and the vapnik-chervonenkis dimension

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T16:54:00.454337Z

Source-reported events for the cited work

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Observation 8b38be50-73ef-4a2c-8b2d-7f7792147ff6 · outbound

This paper cites Curiously fast convergence of some stochastic gradient descent algorithms.

A Unified Analysis for Finite Weight Averaging Curiously fast convergence of some stochastic gradient descent algorithms

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:01.272291Z

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Observation 1266bb4d-2bc0-4315-b96b-94333189b1d7 · outbound

This paper cites Stability and generalization.

A Unified Analysis for Finite Weight Averaging Stability and generalization

Reference 5

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Observation 21a691f9-6b65-4808-82a8-23fb9624a754 · outbound

This paper cites Swad: Domain generalization by seeking flat minima.

A Unified Analysis for Finite Weight Averaging Swad: Domain generalization by seeking flat minima

Reference 6

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Source-reported events for the cited work

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Observation b3612c81-ba1b-411a-9c2d-db254565ec8a · outbound

This paper cites Stability and generalization of learning algorithms that converge to global optima.

A Unified Analysis for Finite Weight Averaging Stability and generalization of learning algorithms that converge to global optima

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:01.238327Z

Source-reported events for the cited work

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Observation d7066da8-849e-435a-bc2f-ee34a5c433b6 · outbound

This paper cites Distribution-free performance bounds for potential function rules.

A Unified Analysis for Finite Weight Averaging Distribution-free performance bounds for potential function rules

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:01.222609Z

Source-reported events for the cited work

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Observation 7a07e84a-4b73-4fd5-b896-8e5cc3203c28 · outbound

This paper cites Loss surfaces, mode connectivity, and fast ensembling of dnns.

A Unified Analysis for Finite Weight Averaging Loss surfaces, mode connectivity, and fast ensembling of dnns

Reference 9

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Source-reported events for the cited work

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Observation eb86b3f6-22cd-4339-b337-aa6e87ac61e9 · outbound

This paper cites Train faster, generalize better: Stability of stochastic gradient descent.

A Unified Analysis for Finite Weight Averaging Train faster, generalize better: Stability of stochastic gradient descent

Reference 10

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Source-reported events for the cited work

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Observation 8ada1cbf-6891-4c76-a604-e6ca83520b18 · outbound

This paper cites Averaging Weights Leads to Wider Optima and Better Generalization.

A Unified Analysis for Finite Weight Averaging Averaging Weights Leads to Wider Optima and Better Generalization

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T16:54:00.492834Z

Source-reported events for the cited work

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Observation 00c961b0-c27f-4edd-89ac-eedf9cea63ad · outbound

This paper cites A Markov Chain Theory Approach to Characterizing the Minimax Optimality of Stochastic Gradient Descent (for Least Squares).

A Unified Analysis for Finite Weight Averaging A Markov Chain Theory Approach to Characterizing the Minimax Optimality of Stochastic Gradient Descent (for Least Squares)

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T16:54:00.497770Z

Source-reported events for the cited work

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Observation 9be090d4-79be-4827-a428-db970eb7fefb · outbound

This paper cites Accelerating stochastic gradient descent for least squares regression.

A Unified Analysis for Finite Weight Averaging Accelerating stochastic gradient descent for least squares regression

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:01.189966Z

Source-reported events for the cited work

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Observation b977b1d3-841f-4dcf-b57e-08016e7632e1 · outbound

This paper cites Parallelizing stochastic gradient descent for least squares regression: mini-batching, averaging, and model misspecification.

A Unified Analysis for Finite Weight Averaging Parallelizing stochastic gradient descent for least squares regression: mini-batching, averaging, and model misspecification

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:01.175357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation db9b41cd-f268-4d2d-b2ac-275b18fd8ccc · outbound

This paper cites Making the last iterate of sgd information theoretically optimal.

A Unified Analysis for Finite Weight Averaging Making the last iterate of sgd information theoretically optimal

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:01.160266Z

Source-reported events for the cited work

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Observation 225b80cb-260d-474e-8139-4b5d0d4015b6 · outbound

This paper cites Stop Wasting My Time! Saving Days of ImageNet and BERT Training with Latest Weight Averaging.

A Unified Analysis for Finite Weight Averaging Stop Wasting My Time! Saving Days of ImageNet and BERT Training with Latest Weight Averaging

Reference 16

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Source-reported events for the cited work

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Observation cc844ecc-39ac-4ef5-bf42-7cc24ffaba81 · outbound

This paper cites Rademacher processes and bounding the risk of function learning.

A Unified Analysis for Finite Weight Averaging Rademacher processes and bounding the risk of function learning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:01.144346Z

Source-reported events for the cited work

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Observation 2435abc2-a31c-44e2-9d3c-7d5702277d5d · outbound

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

A Unified Analysis for Finite Weight Averaging Learning multiple layers of features from tiny images

Reference 18

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Source-reported events for the cited work

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Observation 804549f3-7477-48c0-8ce2-9f22a9b236a6 · outbound

This paper cites Data-dependent stability of stochastic gradient descent.

A Unified Analysis for Finite Weight Averaging Data-dependent stability of stochastic gradient descent

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d2403c57-c1bb-4685-be7e-7ab54f85441a · outbound

This paper cites Linear stochastic approximation: How far does constant step-size and iterate averaging go? In International Conference on Artificial Intelligence and Statistics, pages 1347--1355.

A Unified Analysis for Finite Weight Averaging Linear stochastic approximation: How far does constant step-size and iterate averaging go? In International Conference on Artificial Intelligence and Statistics, pages 1347--1355

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:01.099498Z

Source-reported events for the cited work

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Observation 05eff494-9bd0-4c1d-bc89-ef4e3782ba92 · outbound

This paper cites Gradient-based learning applied to document recognition.

A Unified Analysis for Finite Weight Averaging Gradient-based learning applied to document recognition

Reference 21

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Source-reported events for the cited work

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Observation 2c38a8c0-b1ad-4b1b-a12a-e2e5d6300324 · outbound

This paper cites Fine-grained analysis of stability and generalization for stochastic gradient descent.

A Unified Analysis for Finite Weight Averaging Fine-grained analysis of stability and generalization for stochastic gradient descent

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:01.071058Z

Source-reported events for the cited work

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Observation 3d4f52c8-f451-4d31-b09e-09a568dab058 · outbound

This paper cites Sharper generalization bounds for learning with gradient-dominated objective functions.

A Unified Analysis for Finite Weight Averaging Sharper generalization bounds for learning with gradient-dominated objective functions

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:01.054429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c4be04da-d98d-4da2-8d30-3635f2bb4833 · outbound

This paper cites Trainable weight averaging: Efficient training by optimizing historical solutions.

A Unified Analysis for Finite Weight Averaging Trainable weight averaging: Efficient training by optimizing historical solutions

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:01.038667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 69a677a0-72a8-4b4b-ad59-dae65e62b3a1 · outbound

This paper cites Pac-bayesian model averaging.

A Unified Analysis for Finite Weight Averaging Pac-bayesian model averaging

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:01.023522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2d8ad103-b13e-43b6-aa0e-f23fd5fa9029 · outbound

This paper cites Learning theory: stability is sufficient for generalization and necessary and sufficient for consistency of empirical risk minimization.

A Unified Analysis for Finite Weight Averaging Learning theory: stability is sufficient for generalization and necessary and sufficient for consistency of empirical risk minimization

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:01.008655Z

Source-reported events for the cited work

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Observation e7d84bfe-e076-4ca4-9173-82be776aee22 · outbound

This paper cites A unified convergence analysis for shuffling-type gradient methods.

A Unified Analysis for Finite Weight Averaging A unified convergence analysis for shuffling-type gradient methods

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:00.993540Z

Source-reported events for the cited work

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Observation 91efa5f2-ce02-483b-8256-61eccc7c7d63 · outbound

This paper cites Acceleration of stochastic approximation by averaging.

A Unified Analysis for Finite Weight Averaging Acceleration of stochastic approximation by averaging

Reference 28

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Observation 3e0afcd0-dc6e-42b1-88d8-5cec6c9f95f6 · outbound

This paper cites Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization.

A Unified Analysis for Finite Weight Averaging Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization

Reference 29

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Observation c5181cf0-c478-487a-b504-c5953a9c6052 · outbound

This paper cites Efficient estimations from a slowly convergent robbins-monro process.

A Unified Analysis for Finite Weight Averaging Efficient estimations from a slowly convergent robbins-monro process

Reference 30

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Source-reported events for the cited work

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Observation 6f77e9b0-48f0-47c1-b566-16bd322e9325 · outbound

This paper cites Early weight averaging meets high learning rates for llm pre-training.

A Unified Analysis for Finite Weight Averaging Early weight averaging meets high learning rates for llm pre-training

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:00.958890Z

Source-reported events for the cited work

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Observation ff93f26e-6059-4127-91e5-8c598aa462f2 · outbound

This paper cites Learnability, stability and uniform convergence.

A Unified Analysis for Finite Weight Averaging Learnability, stability and uniform convergence

Reference 32

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Observation a1054d00-1fc8-4e26-be46-b834ec3a9a35 · outbound

This paper cites Without-replacement sampling for stochastic gradient methods.

A Unified Analysis for Finite Weight Averaging Without-replacement sampling for stochastic gradient methods

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:00.934148Z

Source-reported events for the cited work

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Observation 1e2875c5-01cc-4c56-9442-4a9909a439fa · outbound

This paper cites Stochastic gradient descent for non-smooth optimization: Convergence results and optimal averaging schemes.

A Unified Analysis for Finite Weight Averaging Stochastic gradient descent for non-smooth optimization: Convergence results and optimal averaging schemes

Reference 34

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Observation 61d06aa1-0e42-4c1b-bb87-ffea4e4599c9 · outbound

This paper cites Towards Understanding Generalization and Stability Gaps between Centralized and Decentralized Federated Learning.

A Unified Analysis for Finite Weight Averaging Towards Understanding Generalization and Stability Gaps between Centralized and Decentralized Federated Learning

Reference 35

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Source-reported events for the cited work

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Observation e0570f33-cc40-4ca3-95b7-43a0bc5e9792 · outbound

This paper cites Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed Initialization.

A Unified Analysis for Finite Weight Averaging Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed Initialization

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-12T16:54:00.607849Z

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Observation c79cffa4-4473-4728-baa3-6dc614d84e5c · outbound

This paper cites Rethinking the inception architecture for computer vision.

A Unified Analysis for Finite Weight Averaging Rethinking the inception architecture for computer vision

Reference 37

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Observation 5eead994-d598-427a-a348-6015ba3c6042 · outbound

This paper cites Estimation of dependences based on empirical data.

A Unified Analysis for Finite Weight Averaging Estimation of dependences based on empirical data

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:00.898117Z

Source-reported events for the cited work

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Observation 0000e587-c09e-43de-807c-a7ad555a98f7 · outbound

This paper cites Generalization analysis of stochastic weight averaging with general sampling.

A Unified Analysis for Finite Weight Averaging Generalization analysis of stochastic weight averaging with general sampling

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:00.883586Z

Source-reported events for the cited work

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Observation 1e5702c8-aaee-44e1-916b-458f8a02a3b1 · outbound

This paper cites Stability analysis and generalization bounds of adversarial training.

A Unified Analysis for Finite Weight Averaging Stability analysis and generalization bounds of adversarial training

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:00.867799Z

Source-reported events for the cited work

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Observation 079e9836-c274-47f4-a53d-fcc287b4aaaf · outbound

This paper cites Simple stochastic and online gradient descent algorithms for pairwise learning.

A Unified Analysis for Finite Weight Averaging Simple stochastic and online gradient descent algorithms for pairwise learning

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:00.852234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation de925dfc-cf5e-4aae-8cf5-f6453b7a22fd · outbound

This paper cites Stagewise training accelerates convergence of testing error over sgd.

A Unified Analysis for Finite Weight Averaging Stagewise training accelerates convergence of testing error over sgd

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:00.836890Z

Source-reported events for the cited work

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Observation e037fb9c-14c3-4225-8cf0-b7dc17d301a1 · outbound

This paper cites Solving large scale linear prediction problems using stochastic gradient descent algorithms.

A Unified Analysis for Finite Weight Averaging Solving large scale linear prediction problems using stochastic gradient descent algorithms

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-12T16:54:00.639585Z

Source-reported events for the cited work

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Observation f087963e-45e6-40ee-a0a9-e1c482b2e342 · outbound

This paper cites Generalization Error Bounds with Probabilistic Guarantee for SGD in Nonconvex Optimization.

A Unified Analysis for Finite Weight Averaging Generalization Error Bounds with Probabilistic Guarantee for SGD in Nonconvex Optimization

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T16:54:00.643936Z

Source-reported events for the cited work

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Observation 113acb6d-205b-49ab-8eb8-69d16a3af3fd · outbound

This paper cites Stability and generalization of the decentralized stochastic gradient descent ascent algorithm.

A Unified Analysis for Finite Weight Averaging Stability and generalization of the decentralized stochastic gradient descent ascent algorithm

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:54:00.810376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation 53032bf2-b992-4817-8fd1-fca6e2dfab3e · inbound

SeWA: Selective Weight Average via Probabilistic Masking cites this paper.

SeWA: Selective Weight Average via Probabilistic Masking A Unified Analysis for Finite Weight Averaging

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-07T19:24:43.484568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.