:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Damirchi, Hamed, Rodriguez-Opazo, Cristian, Abbasnejad, Ehsan, Zhang, Zhen, Shi, Javen
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2512.22495
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Decomposing Task Vectors for Refined Model Editing
by: Damirchi, Hamed, et al.
Published: (2025)

Truth as a Trajectory: What Internal Representations Reveal About Large Language Model Reasoning
by: Damirchi, Hamed, et al.
Published: (2026)

Synergy and Diversity in CLIP: Enhancing Performance Through Adaptive Backbone Ensembling
by: Rodriguez-Opazo, Cristian, et al.
Published: (2024)

Knowledge Composition using Task Vectors with Learned Anisotropic Scaling
by: Zhang, Frederic Z., et al.
Published: (2024)

Learning Latent Dynamical Causal Processes for Single-Cell Perturbation Prediction
by: Jiang, Wenkang, et al.
Published: (2026)

What Makes a Representation Good for Single-Cell Perturbation Prediction?
by: Jiang, Wenkang, et al.
Published: (2026)

Rethinking State Disentanglement in Causal Reinforcement Learning
by: Cao, Haiyao, et al.
Published: (2024)

When Layers Play the Lottery, all Tickets Win at Initialization
by: Jordao, Artur, et al.
Published: (2023)

Weisfeiler and Leman Go Gambling: Why Expressive Lottery Tickets Win
by: Kummer, Lorenz, et al.
Published: (2025)

Random Masking Finds Winning Tickets for Parameter Efficient Fine-tuning
by: Xu, Jing, et al.
Published: (2024)

Fast Track to Winning Tickets: Repowering One-Shot Pruning for Graph Neural Networks
by: Yue, Yanwei, et al.
Published: (2024)

Uncovering a Winning Lottery Ticket with Continuously Relaxed Bernoulli Gates
by: Tsayag, Itamar, et al.
Published: (2026)

Unlocking the Global Synergies in Low-Rank Adapters
by: Zhang, Zixi, et al.
Published: (2024)

Ensembles of Low-Rank Expert Adapters
by: Li, Yinghao, et al.
Published: (2025)

Towards Higher Effective Rank in Parameter-efficient Fine-tuning using Khatri--Rao Product
by: Albert, Paul, et al.
Published: (2025)

Towards Symmetric Low-Rank Adapters
by: Panoutsos, Tales, et al.
Published: (2025)

Asymmetry in Low-Rank Adapters of Foundation Models
by: Zhu, Jiacheng, et al.
Published: (2024)

BruSLeAttack: A Query-Efficient Score-Based Black-Box Sparse Adversarial Attack
by: Vo, Viet Quoc, et al.
Published: (2024)

Training-Free Bayesianization for Low-Rank Adapters of Large Language Models
by: Shi, Haizhou, et al.
Published: (2024)

Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks
by: Duan, Wenying, et al.
Published: (2024)

Winning Lottery Tickets in Neural Networks via a Quantum-Inspired Classical Algorithm
by: Isogai, Natsuto, et al.
Published: (2026)

Do We Always Need the Simplicity Bias? Looking for Optimal Inductive Biases in the Wild
by: Teney, Damien, et al.
Published: (2025)

Beyond Imitation: Recovering Dense Rewards from Demonstrations
by: Li, Jiangnan, et al.
Published: (2025)

Do Deep Neural Network Solutions Form a Star Domain?
by: Sonthalia, Ankit, et al.
Published: (2024)

Polynomially Over-Parameterized Convolutional Neural Networks Contain Structured Strong Winning Lottery Tickets
by: da Cunha, Arthur, et al.
Published: (2023)

Highway Graph to Accelerate Reinforcement Learning
by: Yin, Zidu, et al.
Published: (2024)

Neural Redshift: Random Networks are not Random Functions
by: Teney, Damien, et al.
Published: (2024)

Winning the Lottery by Preserving Network Training Dynamics with Concrete Ticket Search
by: Arora, Tanay, et al.
Published: (2025)

Aggregating Low Rank Adapters in Federated Fine-tuning
by: Trautmann, Evelyn, et al.
Published: (2025)

Flora: Low-Rank Adapters Are Secretly Gradient Compressors
by: Hao, Yongchang, et al.
Published: (2024)

LoQT: Low-Rank Adapters for Quantized Pretraining
by: Loeschcke, Sebastian, et al.
Published: (2024)

Bayesian Low-Rank LeArning (Bella): A Practical Approach to Bayesian Neural Networks
by: Doan, Bao Gia, et al.
Published: (2024)

Pareto Low-Rank Adapters: Efficient Multi-Task Learning with Preferences
by: Dimitriadis, Nikolaos, et al.
Published: (2024)

AdapterTune: Zero-Initialized Low-Rank Adapters for Frozen Vision Transformers
by: Khazem, Salim
Published: (2026)

A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations
by: Cheng, Hongrong, et al.
Published: (2023)

PoLAR: Polar-Decomposed Low-Rank Adapter Representation
by: Lion, Kai, et al.
Published: (2025)

Mitigating Subject Dependency in EEG Decoding with Subject-Specific Low-Rank Adapters
by: Klein, Timon, et al.
Published: (2025)

Continual Low-Rank Adapters for LLM-based Generative Recommender Systems
by: Yoo, Hyunsik, et al.
Published: (2025)

Multiple Choice Learning of Low-Rank Adapters for Language Modeling
by: Letzelter, Victor, et al.
Published: (2025)

LoRA-Pro: Are Low-Rank Adapters Properly Optimized?
by: Wang, Zhengbo, et al.
Published: (2024)