Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias | Paper Citation Record

Observation 732be365-4dff-4add-b42d-9882b4c2aa93 · outbound

This paper cites The neural tangent kernel in high dimensions: Triple descent and a multi-scale theory of generalization.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias The neural tangent kernel in high dimensions: Triple descent and a multi-scale theory of generalization

Reference 1

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This paper cites powerlaw: a python package for analysis of heavy-tailed distributions.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias powerlaw: a python package for analysis of heavy-tailed distributions

Reference 2

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This paper cites High-dimensional asymptotics of feature learning: How one gradient step improves the representation.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias High-dimensional asymptotics of feature learning: How one gradient step improves the representation

Reference 3

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This paper cites Spectral analysis of large dimensional random matrices, volume 20.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Spectral analysis of large dimensional random matrices, volume 20

Reference 4

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This paper cites Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective

Reference 5

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This paper cites Policy learning from tutorial books via understanding, rehearsing and introspecting.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Policy learning from tutorial books via understanding, rehearsing and introspecting

Reference 6

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Observation 4c1a2e59-b3a3-4706-97d9-24f7df74bdcf · outbound

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

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions

Reference 7

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

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 8

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This paper cites Power-law distributions in empirical data.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Power-law distributions in empirical data

Reference 9

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This paper cites Random Matrix Methods for Machine Learning.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Random Matrix Methods for Machine Learning

Reference 10

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This paper cites Exact expressions for double descent and implicit regularization via surrogate random design.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Exact expressions for double descent and implicit regularization via surrogate random design

Reference 11

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Observation b842158a-6bde-47b9-8cd3-2d033c7022a5 · outbound

This paper cites High-dimensional asymptotics of prediction: Ridge regression and classification.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias High-dimensional asymptotics of prediction: Ridge regression and classification

Reference 12

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Observation aaa82bb2-317c-4990-a6b0-dc45bc686ff6 · outbound

This paper cites Generalizable Adversarial Training via Spectral Normalization.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Generalizable Adversarial Training via Spectral Normalization

Reference 13

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This paper cites Sparsegpt: Massive language models can be accurately pruned in one-shot.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Sparsegpt: Massive language models can be accurately pruned in one-shot

Reference 14

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Observation 516cb8c4-ef5f-40fa-a83d-dba3a8275186 · outbound

This paper cites A framework for few-shot language model evaluation.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias A framework for few-shot language model evaluation

Reference 15

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This paper cites The Llama 3 Herd of Models.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias The Llama 3 Herd of Models

Reference 16

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This paper cites Weidenmüller.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Weidenmüller

Reference 17

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This paper cites The heavy-tail phenomenon in sgd.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias The heavy-tail phenomenon in sgd

Reference 18

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Observation b5f5e7f4-d5ae-4c49-900c-91b7367f2379 · outbound

This paper cites Learning both weights and connections for efficient neural network.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Learning both weights and connections for efficient neural network

Reference 19

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Observation c793f809-80b1-4c22-8434-65beb61ac277 · outbound

This paper cites DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training

Reference 20

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Observation 00bb0077-7dc3-4947-ae3b-6fa3c6953f3a · outbound

This paper cites Surprises in high-dimensional ridgeless least squares interpolation.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Surprises in high-dimensional ridgeless least squares interpolation

Reference 21

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Observation 199ef913-5abb-4be3-a64a-ba70b326263b · outbound

This paper cites Delving deep into rectifiers: Surpassing human-level performance on imagenet classification.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Delving deep into rectifiers: Surpassing human-level performance on imagenet classification

Reference 22

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This paper cites Deep residual learning for image recognition.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Deep residual learning for image recognition

Reference 23

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This paper cites A simple general approach to inference about the tail of a distribution.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias A simple general approach to inference about the tail of a distribution

Reference 24

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Observation 2a5f182c-16d6-4f17-9a83-ac3d183faab2 · outbound

This paper cites Multiplicative noise and heavy tails in stochastic optimization.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Multiplicative noise and heavy tails in stochastic optimization

Reference 25

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This paper cites Generalization bounds using lower tail exponents in stochastic optimizers.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Generalization bounds using lower tail exponents in stochastic optimizers

Reference 26

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This paper cites Universality laws for high-dimensional learning with random features.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Universality laws for high-dimensional learning with random features

Reference 27

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This paper cites From Spikes to Heavy Tails: Unveiling the Spectral Evolution of Neural Networks.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias From Spikes to Heavy Tails: Unveiling the Spectral Evolution of Neural Networks

Reference 28

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Observation 68cb168f-7242-4399-ac8d-acbf1c5368c4 · outbound

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

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Learning multiple layers of features from tiny images

Reference 29

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This paper cites BaWA : Automatic optimizing pruning metric for large language models with balanced weight and activation.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias BaWA : Automatic optimizing pruning metric for large language models with balanced weight and activation

Reference 30

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This paper cites Model Balancing Helps Low-data Training and Fine-tuning.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Model Balancing Helps Low-data Training and Fine-tuning

Reference 31

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This paper cites Lift the veil for the truth: Principal weights emerge after rank reduction for reasoning-focused supervised fine-tuning.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Lift the veil for the truth: Principal weights emerge after rank reduction for reasoning-focused supervised fine-tuning

Reference 32

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This paper cites AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models

Reference 33

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This paper cites Traditional and heavy tailed self regularization in neural network models.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Traditional and heavy tailed self regularization in neural network models

Reference 34

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This paper cites Traditional and Heavy-Tailed Self Regularization in Neural Network Models.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Traditional and Heavy-Tailed Self Regularization in Neural Network Models

Reference 35

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This paper cites Implicit self-regularization in deep neural networks: Evidence from random matrix theory and implications for learning.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Implicit self-regularization in deep neural networks: Evidence from random matrix theory and implications for learning

Reference 36

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This paper cites Martin, Tongsu Peng, and Michael W.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Martin, Tongsu Peng, and Michael W

Reference 37

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This paper cites The generalization error of random features regression: Precise asymptotics and the double descent curve.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias The generalization error of random features regression: Precise asymptotics and the double descent curve

Reference 38

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Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Pointer Sentinel Mixture Models

Reference 39

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This paper cites Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering

Reference 40

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This paper cites Spectral Normalization for Generative Adversarial Networks.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Spectral Normalization for Generative Adversarial Networks

Reference 41

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This paper cites Graph spectra and the detectability of community structure in networks.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Graph spectra and the detectability of community structure in networks

Reference 42

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This paper cites Nonlinear random matrix theory for deep learning.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Nonlinear random matrix theory for deep learning

Reference 43

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Observation 744d6b0b-ed8c-4240-ab1c-b2f5e709fced · outbound

This paper cites AlphaLoRA: Assigning LoRA Experts Based on Layer Training Quality.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias AlphaLoRA: Assigning LoRA Experts Based on Layer Training Quality

Reference 44

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This paper cites Winogrande: An adversarial winograd schema challenge at scale.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Winogrande: An adversarial winograd schema challenge at scale

Reference 45

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This paper cites Stable Rank Normalization for Improved Generalization in Neural Networks and GANs.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Stable Rank Normalization for Improved Generalization in Neural Networks and GANs

Reference 46

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This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 47

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This paper cites A tail-index analysis of stochastic gradient noise in deep neural networks.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias A tail-index analysis of stochastic gradient noise in deep neural networks

Reference 48

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Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Hausdorff dimension, heavy tails, and generalization in neural networks

Reference 49

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This paper cites A Simple and Effective Pruning Approach for Large Language Models.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias A Simple and Effective Pruning Approach for Large Language Models

Reference 50

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Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Pdebench: An extensive benchmark for scientific machine learning

Reference 51

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This paper cites Topics in random matrix theory, volume 132.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Topics in random matrix theory, volume 132

Reference 52

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This paper cites LLaMA: Open and Efficient Foundation Language Models.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias LLaMA: Open and Efficient Foundation Language Models

Reference 53

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This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 54

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This paper cites Tulino and Sergio Verdú.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Tulino and Sergio Verdú

Reference 55

Resolution: verified exact; doi, observed 2026-08-07T06:00:52.011695Z

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Observation d3e1297c-6380-4b2c-bd80-8e5e7b7858c5 · outbound

This paper cites GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T06:00:51.897937Z

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Observation f74a8f92-4d78-4889-8e64-667299ae6b75 · outbound

This paper cites Spectral Evolution and Invariance in Linear-width Neural Networks.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Spectral Evolution and Invariance in Linear-width Neural Networks

Reference 57

Resolution: verified exact; local_arxiv, observed 2026-08-07T06:00:52.295210Z

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

Observation 872597a2-1652-4265-933d-32899998335d · outbound

This paper cites Safe Multi-agent Reinforcement Learning with Natural Language Constraints.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Safe Multi-agent Reinforcement Learning with Natural Language Constraints

Reference 58

Resolution: verified exact; local_arxiv, observed 2026-08-07T06:00:52.276686Z

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 091d8f56-5113-4809-a69e-27e4f77700fc · outbound

This paper cites M3hf: Multi-agent reinforcement learning from multi-phase human feedback of mixed quality.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias M3hf: Multi-agent reinforcement learning from multi-phase human feedback of mixed quality

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:00:52.638534Z

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 080b48e7-3b2d-4bfb-88e9-31aae79215b6 · outbound

This paper cites Tensor programs iv: Feature learning in infinite-width neural networks.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Tensor programs iv: Feature learning in infinite-width neural networks

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T06:00:51.914356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 697b68ac-94da-4602-88c9-c39d7c8cf124 · outbound

This paper cites Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T06:00:51.918076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f151b568-8217-4b12-8117-9873201dc6ca · outbound

This paper cites Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T06:00:51.922284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4db911bd-4f09-498a-92de-43940081b30c · outbound

This paper cites Multimodal commonsense knowledge distillation for visual question answering (student abstract).

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Multimodal commonsense knowledge distillation for visual question answering (student abstract)

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:00:52.617248Z

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 14ceb5be-eff4-4fdb-a232-4850c8e0dbd9 · outbound

This paper cites MAGIC-VQA: Multimodal And Grounded Inference with Commonsense Knowledge for Visual Question Answering.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias MAGIC-VQA: Multimodal And Grounded Inference with Commonsense Knowledge for Visual Question Answering

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T06:00:51.930988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c92a131-5f55-4467-8f83-2e87176298cb · outbound

This paper cites Gonzalez, Kannan Ramchandran, Charles H.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Gonzalez, Kannan Ramchandran, Charles H

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T06:00:51.935251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52659e9c-dcc0-4cf0-ae10-318c363af065 · outbound

This paper cites Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T06:00:51.939296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fb287c6-7cc8-48ce-ab15-3f949fa6e9a2 · outbound

This paper cites Spectral Norm Regularization for Improving the Generalizability of Deep Learning.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Spectral Norm Regularization for Improving the Generalizability of Deep Learning

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T06:00:51.943686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ec66ec6-3ff3-4cd8-8906-5e6c9977da53 · outbound

This paper cites HellaSwag: Can a Machine Really Finish Your Sentence?.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-07T06:00:51.947758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10a65845-56f2-4216-946d-cdc327725998 · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias OPT: Open Pre-trained Transformer Language Models

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T06:00:51.952130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d3e3b2d-0071-41d3-b559-5f9c4f5870b9 · outbound

This paper cites Temperature balancing, layer-wise weight analysis, and neural network training.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Temperature balancing, layer-wise weight analysis, and neural network training

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:00:52.604603Z

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 dbf735e7-d669-4466-9c83-cbdbe3856d02 · outbound

This paper cites Remedy: Recipe merging dynamics in large vision-language models.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Remedy: Recipe merging dynamics in large vision-language models

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:00:52.591848Z

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 a06a3613-6153-410f-9c7b-4f180a284af3 · outbound

This paper cites @esa (Ref.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias @esa (Ref

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T06:00:51.964187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff7bb1ec-01dd-46c3-991f-c446b611261f · outbound

This paper cites an unresolved cited work.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Unresolved cited work

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T06:00:51.968644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45b6c17d-ec5a-4d0a-9971-cfd869263ad5 · outbound

This paper cites training quality.

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias training quality

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-07T06:00:51.972799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Reference resolution

Outbound references

Pith citing papers