Copertina

Modular Delta Merging with Orthogonal Constraints: A Scalable Framework for Continual and Reversible Model Composition

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Khan, Haris, Asif, Sadia, Asif, Shumaila, Karamat, Muhammad Zeeshan, Upadhayaya, Rajesh
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Multi-Agent Framework for Controllable and Protected Generative Content Creation: Addressing Copyright and Provenance in AI-Generated Media
di: Khan, Haris, et al.
Pubblicazione: (2026)

DarkPatterns-LLM: A Multi-Layer Benchmark for Detecting Manipulative and Harmful AI Behavior
di: Asif, Sadia, et al.
Pubblicazione: (2025)

BitFlipScope: Scalable Fault Localization and Recovery for Bit-Flip Corruptions in LLMs
di: Karamat, Muhammad Zeeshan, et al.
Pubblicazione: (2025)

OFMU: Optimization-Driven Framework for Machine Unlearning
di: Asif, Sadia, et al.
Pubblicazione: (2025)

Is Monotonic Sampling Necessary in Diffusion Models?
di: Khan, Muhammad Haris
Pubblicazione: (2026)

SafeBench-Seq: A Homology-Clustered, CPU-Only Baseline for Protein Hazard Screening with Physicochemical/Composition Features and Cluster-Aware Confidence Intervals
di: Khan, Muhammad Haris
Pubblicazione: (2025)

iCost: A Novel Instance Complexity Based Cost-Sensitive Learning Framework
di: Newaz, Asif, et al.
Pubblicazione: (2024)

RefusalGuard: Geometry-Preserving Fine-Tuning for Safety in LLMs
di: Asif, Sadia, et al.
Pubblicazione: (2026)

GCA Framework: A GCC Countries-Grounded Dataset and Agentic Pipeline for Climate Decision Support
di: Sheikh, Muhammad Umer, et al.
Pubblicazione: (2026)

Adversarial robustness of VAEs through the lens of local geometry
di: Khan, Asif, et al.
Pubblicazione: (2022)

UnIT: Scalable Unstructured Inference-Time Pruning for MAC-efficient Neural Inference on MCUs
di: Neth, Ashe, et al.
Pubblicazione: (2025)

Lower-dimensional projections of cellular expression improves cell type classification from single-cell RNA sequencing
di: Umar, Muhammad, et al.
Pubblicazione: (2024)

Twin-Merging: Dynamic Integration of Modular Expertise in Model Merging
di: Lu, Zhenyi, et al.
Pubblicazione: (2024)

FedSCAM (Federated Sharpness-Aware Minimization with Clustered Aggregation and Modulation): Scam-resistant SAM for Robust Federated Optimization in Heterogeneous Environments
di: Rahil, Sameer, et al.
Pubblicazione: (2025)

Unraveling LoRA Interference: Orthogonal Subspaces for Robust Model Merging
di: Zhang, Haobo, et al.
Pubblicazione: (2025)

Toward a Holistic Approach to Continual Model Merging
di: Phan, Hoang, et al.
Pubblicazione: (2025)

Unlocking the Potential of Continual Model Merging: An ODE Perspective
di: Lin, Lihong, et al.
Pubblicazione: (2026)

LCGuard: Latent Communication Guard for Safe KV Sharing in Multi-Agent Systems
di: Asif, Sadia, et al.
Pubblicazione: (2026)

An Explainable Machine Learning Framework for the Accurate Diagnosis of Ovarian Cancer
di: Newaz, Asif, et al.
Pubblicazione: (2023)

Large Language Models for UAVs: Current State and Pathways to the Future
di: Javaid, Shumaila, et al.
Pubblicazione: (2024)

Advances in Intelligent Hearing Aids: Deep Learning Approaches to Selective Noise Cancellation
di: Khan, Haris, et al.
Pubblicazione: (2025)

Tunable MAGMAX: Preference-Aware Model Merging for Continual Learning
di: Hiroshima, Kei, et al.
Pubblicazione: (2026)

MIN-Merging: Merge the Important Neurons for Model Merging
di: Liang, Yunfei
Pubblicazione: (2025)

Fine, I'll Merge It Myself: A Multi-Fidelity Framework for Automated Model Merging
di: Su, Guinan, et al.
Pubblicazione: (2025)

Train with Perturbation, Infer after Merging: A Two-Stage Framework for Continual Learning
di: Qiu, Haomiao, et al.
Pubblicazione: (2025)

Efficient Modular Learning through Naive LoRA Summation: Leveraging Orthogonality in High-Dimensional Models
di: Cao, Zhanhao, et al.
Pubblicazione: (2025)

Towards Scalable SOAP Note Generation: A Weakly Supervised Multimodal Framework
di: Kamal, Sadia, et al.
Pubblicazione: (2025)

Seeing Through VisualBERT: A Causal Adventure on Memetic Landscapes
di: Bandyopadhyay, Dibyanayan, et al.
Pubblicazione: (2024)

How does the Performance of the Data-driven Traffic Flow Forecasting Models deteriorate with Increasing Forecasting Horizon? An Extensive Approach Considering Statistical, Machine Learning and Deep Learning Models
di: Sherfenaz, Amanta, et al.
Pubblicazione: (2025)

K-Merge: Online Continual Merging of Adapters for On-device Large Language Models
di: Shenaj, Donald, et al.
Pubblicazione: (2025)

HoneyBee: A Scalable Modular Framework for Creating Multimodal Oncology Datasets with Foundational Embedding Models
di: Tripathi, Aakash, et al.
Pubblicazione: (2024)

ArrhythmiaVision: Resource-Conscious Deep Learning Models with Visual Explanations for ECG Arrhythmia Classification
di: Baig, Zuraiz, et al.
Pubblicazione: (2025)

Scalable Evaluation and Neural Models for Compositional Generalization
di: Camposampiero, Giacomo, et al.
Pubblicazione: (2025)

Automatic Constraint Policy Optimization based on Continuous Constraint Interpolation Framework for Offline Reinforcement Learning
di: Han, Xinchen, et al.
Pubblicazione: (2026)

MAny: Merge Anything for Multimodal Continual Instruction Tuning
di: Gao, Zijian, et al.
Pubblicazione: (2026)

How to Weight Multitask Finetuning? Fast Previews via Bayesian Model-Merging
di: Maldonado, Hugo Monzón, et al.
Pubblicazione: (2024)

Teaching LLMs How to Learn with Contextual Fine-Tuning
di: Choi, Younwoo, et al.
Pubblicazione: (2025)

Scalable Heterogeneous Graph Learning via Heterogeneous-aware Orthogonal Prototype Experts
di: Zhou, Wei, et al.
Pubblicazione: (2026)

FW-Merging: Scaling Model Merging with Frank-Wolfe Optimization
di: Chen, Hao Mark, et al.
Pubblicazione: (2025)

PSO-Merging: Merging Models Based on Particle Swarm Optimization
di: Zhang, Kehao, et al.
Pubblicazione: (2025)