Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T06:00:51.972799Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 1 inbound Pith citation observation for arXiv:2506.06280.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T06:00:51.972799Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T18:12:34.296158Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T18:12:37.393299Z
74 of 74 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 732be365-4dff-4add-b42d-9882b4c2aa93 · outbound
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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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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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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Observation d2b71af2-15fa-4273-bf6a-c0b305124183 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Spectral analysis of large dimensional random matrices, volume 20
Reference 4
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Observation 079aa85f-37d3-42bc-9805-d65cb46ea714 · outbound
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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Observation f8a57f33-5050-4002-a3cc-a5801f2450ed · outbound
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
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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Observation cd9ffd53-d7fd-4819-b0e1-7d813db58903 · outbound
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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Observation 57227f9d-6a41-4752-b620-55096ec2bce5 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Power-law distributions in empirical data
Reference 9
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Observation 36517b75-37e1-4bbd-925c-c0bad721a8d5 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Random Matrix Methods for Machine Learning
Reference 10
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Observation 139422d4-0e27-4663-9c77-066691da0a59 · outbound
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
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
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Generalizable Adversarial Training via Spectral Normalization
Reference 13
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Observation c8a3653e-7d44-4211-835d-4868a2301122 · outbound
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
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias A framework for few-shot language model evaluation
Reference 15
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Observation 5cc94017-8631-4d1d-810c-50bfb72c55d5 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias The Llama 3 Herd of Models
Reference 16
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Observation be6a616a-fca2-4fbe-9141-285b976a2f4d · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Weidenmüller
Reference 17
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Observation 5f29d374-3906-4217-92b8-7cf47a2434b4 · outbound
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
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
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
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
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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Observation ff2bf95b-9f60-47c0-8bbe-4d55ad69f60a · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Deep residual learning for image recognition
Reference 23
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Observation 9beb227d-8103-442c-b5da-45de1b9d0955 · outbound
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
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Multiplicative noise and heavy tails in stochastic optimization
Reference 25
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Observation 9e18fbb4-472c-4c7b-a262-030bd38dfa49 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Generalization bounds using lower tail exponents in stochastic optimizers
Reference 26
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Observation 845f4b70-fd76-4090-847e-6c713ff9d976 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Universality laws for high-dimensional learning with random features
Reference 27
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Observation 8dc60cf9-907f-4387-b44f-1c1320169106 · outbound
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
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Learning multiple layers of features from tiny images
Reference 29
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Observation deeced84-2447-45c9-9695-85d85c712414 · outbound
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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Observation 2aa71a65-f902-44b3-8afb-213cf0756125 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Model Balancing Helps Low-data Training and Fine-tuning
Reference 31
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Observation d80cfb40-4173-4dc2-894f-dea92483912a · outbound
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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Observation ea833ff8-10f9-4fb1-90b2-905f69a19ac9 · outbound
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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Observation 62bfd72d-bddc-4a8c-8c7c-12af1970c10c · outbound
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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Observation 0d8389a0-9de5-4f32-9237-be8fd637dcb0 · outbound
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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Observation 626276c1-0762-4181-958d-aa4aefe79aec · outbound
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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Observation 8d4de6ec-ac16-4ad6-b8fb-2e982a794a35 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Martin, Tongsu Peng, and Michael W
Reference 37
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Observation ee2ba575-99ff-4eb0-bb52-a6a9e8012a83 · outbound
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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Observation e76c3c1a-d9ec-4ccd-b069-e83f7c537ecf · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Pointer Sentinel Mixture Models
Reference 39
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Observation e1bc72a5-4fc6-431f-b052-15ef7478c07d · outbound
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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Observation adf9ab93-26ef-4299-a41c-a761b1d1ec43 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Spectral Normalization for Generative Adversarial Networks
Reference 41
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Observation 632d4784-38a3-402a-a7e8-1e30c44690f5 · outbound
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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Observation 708f47bc-fe77-41ab-aa44-50896327ba50 · outbound
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
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias AlphaLoRA: Assigning LoRA Experts Based on Layer Training Quality
Reference 44
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Observation eb84b51b-2809-43a3-8810-e1849c8281b3 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Winogrande: An adversarial winograd schema challenge at scale
Reference 45
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Observation 154b86d8-c19b-42e9-a583-5864e3a61a2a · outbound
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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Observation bf5b3c2e-1c94-40b0-ab48-ae90404a3087 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Very Deep Convolutional Networks for Large-Scale Image Recognition
Reference 47
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Observation b53b2516-bd26-4c69-9e5a-016d0dc37f82 · outbound
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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Observation ea37a1a5-30e8-4607-aa0b-33fb9db059e5 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Hausdorff dimension, heavy tails, and generalization in neural networks
Reference 49
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Observation 762e8aa0-feef-47a5-9815-7a3360b93b34 · outbound
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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Observation d9d77f4e-3809-46ce-a750-5c70a0c0ced9 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Topics in random matrix theory, volume 132
Reference 52
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Observation c96c9f74-da76-4aa9-bb53-120b22903b5d · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias LLaMA: Open and Efficient Foundation Language Models
Reference 53
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Observation a26140bb-49b8-448c-929f-9b4f6fbf748d · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Llama 2: Open Foundation and Fine-Tuned Chat Models
Reference 54
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Observation b0cb3bab-38ca-4253-9122-3a4677239a24 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Tulino and Sergio Verdú
Reference 55
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Observation d3e1297c-6380-4b2c-bd80-8e5e7b7858c5 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Reference 56
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Observation f74a8f92-4d78-4889-8e64-667299ae6b75 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Spectral Evolution and Invariance in Linear-width Neural Networks
Reference 57
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Observation 872597a2-1652-4265-933d-32899998335d · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Safe Multi-agent Reinforcement Learning with Natural Language Constraints
Reference 58
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Observation 091d8f56-5113-4809-a69e-27e4f77700fc · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias M3hf: Multi-agent reinforcement learning from multi-phase human feedback of mixed quality
Reference 59
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Observation 080b48e7-3b2d-4bfb-88e9-31aae79215b6 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Tensor programs iv: Feature learning in infinite-width neural networks
Reference 60
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Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer
Reference 61
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Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace
Reference 62
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Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Multimodal commonsense knowledge distillation for visual question answering (student abstract)
Reference 63
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Observation 14ceb5be-eff4-4fdb-a232-4850c8e0dbd9 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias MAGIC-VQA: Multimodal And Grounded Inference with Commonsense Knowledge for Visual Question Answering
Reference 64
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Observation 6c92a131-5f55-4467-8f83-2e87176298cb · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Gonzalez, Kannan Ramchandran, Charles H
Reference 65
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Observation 52659e9c-dcc0-4cf0-ae10-318c363af065 · outbound
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
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Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Spectral Norm Regularization for Improving the Generalizability of Deep Learning
Reference 67
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Observation 3ec66ec6-3ff3-4cd8-8906-5e6c9977da53 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias HellaSwag: Can a Machine Really Finish Your Sentence?
Reference 68
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Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias OPT: Open Pre-trained Transformer Language Models
Reference 69
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Observation 1d3e3b2d-0071-41d3-b559-5f9c4f5870b9 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Temperature balancing, layer-wise weight analysis, and neural network training
Reference 70
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Observation dbf735e7-d669-4466-9c83-cbdbe3856d02 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Remedy: Recipe merging dynamics in large vision-language models
Reference 71
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Observation a06a3613-6153-410f-9c7b-4f180a284af3 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias @esa (Ref
Reference 72
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Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias Unresolved cited work
Reference 73
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Observation 45b6c17d-ec5a-4d0a-9971-cfd869263ad5 · outbound
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias training quality
Reference 74
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Observation 4f7a8ce7-cf02-445f-9d95-afe313e114ac · inbound
S3LoRA: Safe Spectral Sharpness-Guided Pruning in Adaptation of Agent Planner Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias
Reference 14
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