Copertina

Neural Organ Transplantation (NOT): Checkpoint-Based Modular Adaptation for Transformer Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Al-Zuraiqi, Ahmad
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

FERI: A Multitask-based Fairness Achieving Algorithm with Applications to Fair Organ Transplantation
di: Li, Can, et al.
Pubblicazione: (2023)

Neural ODE and SDE Models for Adaptation and Planning in Model-Based Reinforcement Learning
di: Han, Chao, et al.
Pubblicazione: (2026)

Transformers as Neural Operators for Solutions of Differential Equations with Finite Regularity
di: Shih, Benjamin, et al.
Pubblicazione: (2024)

Training Neural Networks for Modularity aids Interpretability
di: Golechha, Satvik, et al.
Pubblicazione: (2024)

Studying Cross-cluster Modularity in Neural Networks
di: Golechha, Satvik, et al.
Pubblicazione: (2025)

GoldenTransformer: A Modular Fault Injection Framework for Transformer Robustness Research
di: Howard, Luke
Pubblicazione: (2025)

Engineering Verifiable Modularity in Transformers via Per-Layer Supervision
di: Kerce, J. Clayton
Pubblicazione: (2026)

READ: Recurrent Adaptation of Large Transformers
di: Nguyen, John, et al.
Pubblicazione: (2023)

On the Structural Limitations of Weight-Based Neural Adaptation and the Role of Reversible Behavioral Learning
di: Konduru, Pardhu Sri Rushi Varma
Pubblicazione: (2026)

Learning Modular Exponentiation with Transformers
di: Africa, David Demitri, et al.
Pubblicazione: (2025)

Mashup Learning: Faster Finetuning by Remixing Past Checkpoints
di: Vaina, Sofia Maria Lo Cicero, et al.
Pubblicazione: (2026)

AttentionSmithy: A Modular Framework for Rapid Transformer Development and Customization
di: Cranney, Caleb, et al.
Pubblicazione: (2025)

Uncovering a Universal Abstract Algorithm for Modular Addition in Neural Networks
di: McCracken, Gavin, et al.
Pubblicazione: (2025)

DHA: Learning Decoupled-Head Attention from Transformer Checkpoints via Adaptive Heads Fusion
di: Chen, Yilong, et al.
Pubblicazione: (2024)

Towards Empirical Interpretation of Internal Circuits and Properties in Grokked Transformers on Modular Polynomials
di: Furuta, Hiroki, et al.
Pubblicazione: (2024)

Model Fusion via Neuron Transplantation
di: Öz, Muhammed, et al.
Pubblicazione: (2025)

AdaDim: Dimensionality Adaptation for SSL Representational Dynamics
di: Kokilepersaud, Kiran, et al.
Pubblicazione: (2025)

FAA-CLIP: Federated Adversarial Adaptation of CLIP
di: Wu, Yihang, et al.
Pubblicazione: (2025)

Plug-and-Play Transformer Modules for Test-Time Adaptation
di: Chang, Xiangyu, et al.
Pubblicazione: (2024)

Modular Boundaries in Recurrent Neural Networks
di: Tanner, Jacob, et al.
Pubblicazione: (2023)

Dispatch-Aware Ragged Attention for Pruned Vision Transformers
di: Abdellatif, Seifeldin, et al.
Pubblicazione: (2026)

Boosting Cross-problem Generalization in Diffusion-Based Neural Combinatorial Solver via Inference Time Adaptation
di: Lei, Haoyu, et al.
Pubblicazione: (2025)

SURGE: Surrogate Gradient Adaptation in Binary Neural Networks
di: Huang, Haoyu, et al.
Pubblicazione: (2026)

Unlocking Emergent Modularity in Large Language Models
di: Qiu, Zihan, et al.
Pubblicazione: (2023)

CoSA: Compressed Sensing-Based Adaptation of Large Language Models
di: Wei, Songtao, et al.
Pubblicazione: (2026)

Simulations of Common Unsupervised Domain Adaptation Algorithms for Image Classification
di: Chaddad, Ahmad, et al.
Pubblicazione: (2025)

Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features
di: Faisal, Aseer Al
Pubblicazione: (2025)

FocusLearn: Fully-Interpretable, High-Performance Modular Neural Networks for Time Series
di: Su, Qiqi, et al.
Pubblicazione: (2023)

NASP-T: A Fuzzy Neuro-Symbolic Transformer for Logic-Constrained Aviation Safety Report Classification
di: Machot, Fadi Al, et al.
Pubblicazione: (2025)

Lightweight Geometric Adaptation for Training Physics-Informed Neural Networks
di: An, Kang, et al.
Pubblicazione: (2026)

Spectral Transformer Neural Processes
di: Chen, Xianhe, et al.
Pubblicazione: (2026)

Weight Space Representation Learning via Neural Field Adaptation
di: Yang, Zhuoqian, et al.
Pubblicazione: (2025)

A Lightweight DL Model for Smart Grid Power Forecasting with Feature and Resolution Mismatch
di: Al-Shareeda, Sarah, et al.
Pubblicazione: (2025)

Neural Decompiling of Tracr Transformers
di: Thurnherr, Hannes, et al.
Pubblicazione: (2024)

Transformers are Graph Neural Networks
di: Joshi, Chaitanya K.
Pubblicazione: (2025)

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation
di: Zhou, Xinyu, et al.
Pubblicazione: (2025)

Beyond Components: Singular Vector-Based Interpretability of Transformer Circuits
di: Ahmad, Areeb, et al.
Pubblicazione: (2025)

METHOD: Modular Efficient Transformer for Health Outcome Discovery
di: Qian, Linglong, et al.
Pubblicazione: (2025)

Cliqueformer: Model-Based Optimization with Structured Transformers
di: Kuba, Jakub Grudzien, et al.
Pubblicazione: (2024)

SeqBattNet: A Discrete-State Physics-Informed Neural Network with Aging Adaptation for Battery Modeling
di: Tran, Khoa, et al.
Pubblicazione: (2025)