Paper Citation Record · LEDGER

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes

As of 8 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 2 inbound Pith citation observations for arXiv:2508.00180.

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

pith.paper-citation-record.v1
2508.00180 v1

Coverage vector

measured 83 of 83 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:23:52.037279Z

measured 85 of 85 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-01T06:36:46.924135Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:49:58.438161Z

Reference resolution

83 of 83 outbound references displayed

verified exact0
verified fuzzy33
unresolved50
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 77d65f5c-2ad6-45b1-8128-7fa0df78b51b · outbound

This paper cites Program Synthesis with Large Language Models.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Program Synthesis with Large Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:45.651809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2fd7dd10-ca30-4ebc-995a-d843395cfb1d · outbound

This paper cites High-dimensional limit theorems for sgd: Effective dynamics and critical scaling.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes High-dimensional limit theorems for sgd: Effective dynamics and critical scaling

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:45.744826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 896df6f7-d37c-412f-96ea-fef7358e4f68 · outbound

This paper cites Provable guarantees for generative behavior cloning: Bridging low-level stability and high-level behavior.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Provable guarantees for generative behavior cloning: Bridging low-level stability and high-level behavior

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:45.821133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93c7e947-9878-47dd-9ea3-2962ab80e862 · outbound

This paper cites Butterfly effects of sgd noise: Error amplification in behavior cloning and autoregression.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Butterfly effects of sgd noise: Error amplification in behavior cloning and autoregression

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:45.847970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f3e6366-e1a1-40cf-96b8-f73a2e26bc03 · outbound

This paper cites Approximation methods which converge with probability one.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Approximation methods which converge with probability one

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.713434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 71712a5f-ec88-4c23-b972-f6cb2bfc0284 · outbound

This paper cites How to scale your ema.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes How to scale your ema

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.704441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 739fa8a4-4a7e-4faf-9323-205d53801095 · outbound

This paper cites LEGAL-BERT: The Muppets straight out of Law School.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes LEGAL-BERT: The Muppets straight out of Law School

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:46.241953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 658e397c-b1a2-46e6-a480-ba086aed9129 · outbound

This paper cites Incorrect baseline evaluations call into question recent llm-rl claims, 2025.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Incorrect baseline evaluations call into question recent llm-rl claims, 2025

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.694876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1693cfb4-1984-47db-a98a-c47900d5666c · outbound

This paper cites Learning to Generate Better Than Your LLM.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Learning to Generate Better Than Your LLM

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:46.465760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e92d7ade-133c-4a6c-a0a6-5c32c8cc73db · outbound

This paper cites Bidirectional looking with a novel double exponential moving average to adaptive and non-adaptive momentum optimizers.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Bidirectional looking with a novel double exponential moving average to adaptive and non-adaptive momentum optimizers

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.685663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 62db7694-fe61-409d-9657-a56932319d04 · outbound

This paper cites Double/debiased machine learning for treatment and structural parameters, 2018.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Double/debiased machine learning for treatment and structural parameters, 2018

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:46.595345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8083e651-f737-47e3-8a4c-7f1cb04ceaeb · outbound

This paper cites Deep reinforcement learning from human preferences.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Deep reinforcement learning from human preferences

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:46.712637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6e0a726-cff1-4a2a-b042-9c8d44377b3c · outbound

This paper cites BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:46.829935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfa83e9a-5329-42f5-a3fc-6079bdc55943 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Training Verifiers to Solve Math Word Problems

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:46.868383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d96bd46-3797-412d-a50d-1b9585d41287 · outbound

This paper cites Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:46.940838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39618f0a-9a58-4c81-92e1-093b7557d8d4 · outbound

This paper cites Saga: A fast incremental gradient method with support for non-strongly convex composite objectives.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Saga: A fast incremental gradient method with support for non-strongly convex composite objectives

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:47.049340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 289142f1-3423-4b30-9061-e1b4c64b5796 · outbound

This paper cites Averaged least-mean-squares: Bias-variance trade-offs and optimal sampling distributions.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Averaged least-mean-squares: Bias-variance trade-offs and optimal sampling distributions

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.660256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ccb16d40-0472-4d07-b715-80d9f10420f0 · outbound

This paper cites Harder, better, faster, stronger convergence rates for least-squares regression.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Harder, better, faster, stronger convergence rates for least-squares regression

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.650886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 13b7bb9e-5939-40de-b10a-ca467174d357 · outbound

This paper cites Adaptive subgradient methods for online learning and stochastic optimization.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Adaptive subgradient methods for online learning and stochastic optimization

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:47.286455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dfb3620-86a9-4642-8b03-f979ba971b2f · outbound

This paper cites Is behavior cloning all you need? understanding horizon in imitation learning.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Is behavior cloning all you need? understanding horizon in imitation learning

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.636518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 98952c78-f52a-43a7-8762-b8befb25b1ea · outbound

This paper cites The Llama 3 Herd of Models.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes The Llama 3 Herd of Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:47.454252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d917c7c-1e02-4cba-b043-0fc3e628a464 · outbound

This paper cites Bootstrap your own latent-a new approach to self-supervised learning.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Bootstrap your own latent-a new approach to self-supervised learning

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.628324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c7d64f01-90ce-482c-9e60-ac4c9f22bc6d · outbound

This paper cites Shampoo: Preconditioned stochastic tensor optimization.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Shampoo: Preconditioned stochastic tensor optimization

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:47.675863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5a3b82a-2d64-46fe-9b46-5323414f16b9 · outbound

This paper cites Measuring massive multitask language understanding.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Measuring massive multitask language understanding

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:47.715586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25f37361-a597-4e58-b341-fbe7cadf4fe0 · outbound

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

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Averaging Weights Leads to Wider Optima and Better Generalization

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:47.788636Z

Source-reported events for the cited work

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Observation 2b320dce-cf3e-4c70-ac64-2d6cafb1a769 · outbound

This paper cites Neural tangent kernel: Convergence and generalization in neural networks.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Neural tangent kernel: Convergence and generalization in neural networks

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:47.969468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1896506d-1216-420a-8999-dadc4a973a61 · outbound

This paper cites Accelerating stochastic gradient descent using predictive variance reduction.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Accelerating stochastic gradient descent using predictive variance reduction

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:48.111032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96672192-4172-4668-8c19-b26010b8810b · outbound

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

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Stop Wasting My Time! Saving Days of ImageNet and BERT Training with Latest Weight Averaging

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:48.286379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09d638c1-2edc-4312-bfa7-39834e488387 · outbound

This paper cites No train no gain: Revisiting efficient training algorithms for transformer-based language models.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes No train no gain: Revisiting efficient training algorithms for transformer-based language models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.594443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 27489973-0d4f-4fca-bbb8-1ddfbc324af7 · outbound

This paper cites Gemma 3 Technical Report.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Gemma 3 Technical Report

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:48.550625Z

Source-reported events for the cited work

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Observation edf4b9f7-060b-40ef-b8ac-f239fde50a20 · outbound

This paper cites Analyzing and Improving the Training Dynamics of Diffusion Models.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Analyzing and Improving the Training Dynamics of Diffusion Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:48.659364Z

Source-reported events for the cited work

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Observation 32dc7719-8ef9-4931-9a68-79d2831431ec · outbound

This paper cites Adam: A Method for Stochastic Optimization.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Adam: A Method for Stochastic Optimization

Reference 32

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Unavailable: canonical work link unavailable.

Observation 8798bd86-4e58-4e5f-b18c-fc4f255e4fee · outbound

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EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-06T10:23:52.585249Z

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Observation a4e38958-5226-4474-ad47-caaca1076791 · outbound

This paper cites Statistical inference for ergodic diffusion processes.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Statistical inference for ergodic diffusion processes

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.576321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c6e724a6-2d50-4fcb-8afe-e57fca99404a · outbound

This paper cites Gonzalez, Hao Zhang, and Ion Stoica.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Gonzalez, Hao Zhang, and Ion Stoica

Reference 35

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Observation a0a7993c-f5cd-4937-9f93-9d7ed7c6069b · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 36

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Observation 66afda0a-b3f5-4f90-ae01-639a92707c1b · outbound

This paper cites Brownian motion, martingales, and stochastic calculus.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Brownian motion, martingales, and stochastic calculus

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.561802Z

Source-reported events for the cited work

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Observation f31e223d-ed04-4978-b17c-ea41dc475b74 · outbound

This paper cites Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks

Reference 38

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Source-reported events for the cited work

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Observation 9bf4a260-eafb-4224-a215-816eb2051fb1 · outbound

This paper cites Biobert: a pre-trained biomedical language representation model for biomedical text mining.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Biobert: a pre-trained biomedical language representation model for biomedical text mining

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:49.577990Z

Source-reported events for the cited work

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Observation 02ffbe8d-dd24-4b18-a2f7-d2fa7f8dec37 · outbound

This paper cites Theory of point estimation.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Theory of point estimation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.548229Z

Source-reported events for the cited work

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Observation 00607ca9-db1b-4724-b9f2-5151132513de · outbound

This paper cites Stochastic modified equations and adaptive stochastic gradient algorithms.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Stochastic modified equations and adaptive stochastic gradient algorithms

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.539762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 314f98bd-a0a5-47c9-86d3-210482100d3b · outbound

This paper cites Switch EMA: A Free Lunch for Better Flatness and Sharpness.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Switch EMA: A Free Lunch for Better Flatness and Sharpness

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:49.973613Z

Source-reported events for the cited work

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EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Statistics of random processes: I

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.529338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation eb64e063-3c2a-47b7-b32f-7ce796c46572 · outbound

This paper cites Statistics of random processes II: Applications, volume 6.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Statistics of random processes II: Applications, volume 6

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.520280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3ae028ca-7d4f-4477-91b8-157b9104151d · outbound

This paper cites Improving Large Language Model Fine-tuning for Solving Math Problems.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Improving Large Language Model Fine-tuning for Solving Math Problems

Reference 45

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Source-reported events for the cited work

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This paper cites Decoupled Weight Decay Regularization.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Decoupled Weight Decay Regularization

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:50.449308Z

Source-reported events for the cited work

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Observation 9354b131-9533-4e5d-b039-e6df4926a553 · outbound

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EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Sgdr: Stochastic gradient descent with warm restarts

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.510379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4c731e40-810a-4bef-a614-2d93dff90ae5 · outbound

This paper cites On the sdes and scaling rules for adaptive gradient algorithms.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes On the sdes and scaling rules for adaptive gradient algorithms

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.500602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8218bda6-13f4-49a8-b80a-f68c516c1237 · outbound

This paper cites A kernel-based view of language model fine-tuning.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes A kernel-based view of language model fine-tuning

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.490518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 003eaaf9-a0fc-42a3-bf0e-6e5dfb9aa8d6 · outbound

This paper cites Continuous-time limit of stochastic gradient descent revisited.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Continuous-time limit of stochastic gradient descent revisited

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.480815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6d91ba18-c107-4815-8ff2-1f4b5fa364c7 · outbound

This paper cites Revisiting Small Batch Training for Deep Neural Networks.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Revisiting Small Batch Training for Deep Neural Networks

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:51.098062Z

Source-reported events for the cited work

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Observation 0c8c19e7-d57e-4c68-b2db-ed8c2d61560a · outbound

This paper cites Scaling data-constrained language models.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Scaling data-constrained language models

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.471882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 20f73c62-3c1d-4e41-b91a-35c3b02ad8bf · outbound

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EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Smoothing data with faster moving averages

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.461579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bc56b3ed-8cf8-43b1-a2bb-ef7d4ee063bc · outbound

This paper cites Introductory lectures on convex optimization: A basic course, volume 87.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Introductory lectures on convex optimization: A basic course, volume 87

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:51.248593Z

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Observation 2c4a8d23-c44c-4622-a190-d8c2f52971b7 · outbound

This paper cites The AdEMAMix Optimizer: Better, Faster, Older.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes The AdEMAMix Optimizer: Better, Faster, Older

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:51.290978Z

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Observation 903ef485-a89c-4c09-a73f-5d0fed6b6d38 · outbound

This paper cites Acceleration of stochastic approximation by averaging.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Acceleration of stochastic approximation by averaging

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:51.355993Z

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Observation f677e7bf-abe4-4933-aff1-388584f22d12 · outbound

This paper cites Early stopping-but when? In Neural Networks: Tricks of the trade, pages 55--69.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Early stopping-but when? In Neural Networks: Tricks of the trade, pages 55--69

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.442277Z

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Observation 2be369ba-6019-4b73-b08c-5dbffc90b2f0 · outbound

This paper cites Non-convex learning via stochastic gradient langevin dynamics: a nonasymptotic analysis.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Non-convex learning via stochastic gradient langevin dynamics: a nonasymptotic analysis

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.433596Z

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Observation 0701a113-76b3-454d-b5fa-9eb10308df36 · outbound

This paper cites Breaking the data barrier: a review of deep learning techniques for democratizing ai with small datasets.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Breaking the data barrier: a review of deep learning techniques for democratizing ai with small datasets

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.424548Z

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Observation 2992878c-c911-417e-820b-29eedb5144d3 · outbound

This paper cites A stochastic approximation method.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes A stochastic approximation method

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:51.615896Z

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Observation 78351fb6-0bc2-4d51-b568-5f4c6915fac4 · outbound

This paper cites Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier: Autoregressive and Imitation Learning under Misspecification.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier: Autoregressive and Imitation Learning under Misspecification

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:51.683656Z

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Observation aa313c8a-d8d0-4e06-a8a6-aee62b6b93d6 · outbound

This paper cites Efficient reductions for imitation learning.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Efficient reductions for imitation learning

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:51.748205Z

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This paper cites A reduction of imitation learning and structured prediction to no-regret online learning.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes A reduction of imitation learning and structured prediction to no-regret online learning

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:51.794840Z

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Observation c787143b-5a90-431d-8842-6c8a82b87ebf · outbound

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

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Efficient estimations from a slowly convergent robbins-monro process

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:51.859645Z

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Observation 8a87a096-54f8-4fa8-9708-00f1012e76a9 · outbound

This paper cites Training trajectories, mini-batch losses and the curious role of the learning rate.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Training trajectories, mini-batch losses and the curious role of the learning rate

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:51.923341Z

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This paper cites Minimizing finite sums with the stochastic average gradient.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Minimizing finite sums with the stochastic average gradient

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.393897Z

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Observation f8128de6-fac8-49a3-8b6f-0d8fac1217cd · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:51.990831Z

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Observation 0aba7616-5249-4866-8dd2-021dbb866380 · outbound

This paper cites Super-convergence: Very fast training of neural networks using large learning rates.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Super-convergence: Very fast training of neural networks using large learning rates

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.384775Z

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Observation 543628a2-0b7b-4f9d-9b0b-1d21292efd3a · outbound

This paper cites Qwen2 Technical Report.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Qwen2 Technical Report

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:51.996778Z

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Observation 38f0b125-781e-485d-97f1-451cb290f238 · outbound

This paper cites The calculus of variations.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes The calculus of variations

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.376386Z

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Observation 49c508b4-ce11-4e0d-991f-627df44efe78 · outbound

This paper cites Position: Will we run out of data? limits of llm scaling based on human-generated data.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Position: Will we run out of data? limits of llm scaling based on human-generated data

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.367049Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 06956e02-6b0b-4a44-a0a3-53510cf559dd · outbound

This paper cites Trl: Transformer reinforcement learning.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Trl: Transformer reinforcement learning

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:52.005485Z

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Observation 5546061b-d571-40d7-bca1-0c66a26c29b5 · outbound

This paper cites SOAP: Improving and Stabilizing Shampoo using Adam.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes SOAP: Improving and Stabilizing Shampoo using Adam

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:52.008343Z

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Observation 49120fe7-4a2a-405e-88dd-11a465f3e2d1 · outbound

This paper cites Superglue: A stickier benchmark for general-purpose language understanding systems.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Superglue: A stickier benchmark for general-purpose language understanding systems

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:52.011334Z

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Observation 58e3edb6-777e-47a0-b3a9-3d29950c1ede · outbound

This paper cites ema-pytorch: A simple way to keep track of an exponential moving average (ema) version of your pytorch model.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes ema-pytorch: A simple way to keep track of an exponential moving average (ema) version of your pytorch model

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.347595Z

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Observation 62e13964-feeb-487e-83ed-eef21cfeb3f8 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Chain-of-thought prompting elicits reasoning in large language models

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:52.017038Z

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Observation f8442a29-4453-4dc7-8b4c-e7fde02af4a7 · outbound

This paper cites The large-sample distribution of the likelihood ratio for testing composite hypotheses.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes The large-sample distribution of the likelihood ratio for testing composite hypotheses

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.332725Z

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Observation be69d861-2136-41e0-9408-812959c91b77 · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:52.022460Z

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Observation a1d1c380-9e97-4495-84a3-df5afbb5e8af · outbound

This paper cites On early stopping in gradient descent learning.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes On early stopping in gradient descent learning

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.323689Z

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Observation cef1f308-1976-48a3-8571-c6680040d92a · outbound

This paper cites Which algorithmic choices matter at which batch sizes? insights from a noisy quadratic model.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Which algorithmic choices matter at which batch sizes? insights from a noisy quadratic model

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.314284Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 31cb124b-8863-4e1e-92e1-f0b93d1a78dd · outbound

This paper cites How Does Critical Batch Size Scale in Pre-training?.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes How Does Critical Batch Size Scale in Pre-training?

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:52.031002Z

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Observation 18f89d3e-88e6-4ce6-b4be-7b8479fc860d · outbound

This paper cites Parameter identification for fractional ornstein--uhlenbeck processes based on discrete observation.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes Parameter identification for fractional ornstein--uhlenbeck processes based on discrete observation

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:23:52.304477Z

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Observation 203f65ac-9dcb-4883-b707-fd0aed7e2406 · outbound

This paper cites write newline.

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes write newline

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-06T10:23:52.037279Z

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Pith citing papers

Observation 374ef32c-908d-4e31-9576-f1af93cdc24d · inbound

Training for the Model You Return: Improving Optimization for Iterate-Averaged Language Models cites this paper.

Training for the Model You Return: Improving Optimization for Iterate-Averaged Language Models EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-04T16:49:58.439604Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a0734cca-aa0f-4edd-a9cf-aafd1e765fd1 · inbound

Training for the Model You Return: Improving Optimization for Iterate-Averaged Language Models cites this paper.

Training for the Model You Return: Improving Optimization for Iterate-Averaged Language Models EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-01T09:25:41.338906Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.