:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Gao, Shangqian, Hua, Ting, Shirkavand, Reza, Lin, Chi-Heng, Tang, Zheng, Li, Zhengao, Yuan, Longge, Li, Fangyi, Zhang, Zeyu, Ganjdanesh, Alireza, Qian, Lou, Jie, Xu, Hsu, Yen-Chang
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computation and Language
Online Access:	https://arxiv.org/abs/2501.15316
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models
by: Ganjdanesh, Alireza, et al.
Published: (2024)

Jointly Training and Pruning CNNs via Learnable Agent Guidance and Alignment
by: Ganjdanesh, Alireza, et al.
Published: (2024)

Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models
by: Shirkavand, Reza, et al.
Published: (2024)

Cost-Aware Contrastive Routing for LLMs
by: Shirkavand, Reza, et al.
Published: (2025)

From Pixels to Prose: A Large Dataset of Dense Image Captions
by: Singla, Vasu, et al.
Published: (2024)

DISP-LLM: Dimension-Independent Structural Pruning for Large Language Models
by: Gao, Shangqian, et al.
Published: (2024)

Privacy-Preserving LLMs Routing
by: Wu, Xidong, et al.
Published: (2026)

Mixture of Efficient Diffusion Experts Through Automatic Interval and Sub-Network Selection
by: Ganjdanesh, Alireza, et al.
Published: (2024)

Capability Self-Assessment: Teaching LLMs to Know Their Limits
by: Yang, Haoyan, et al.
Published: (2026)

FlexiGPT: Pruning and Extending Large Language Models with Low-Rank Weight Sharing
by: Smith, James Seale, et al.
Published: (2025)

MoDeGPT: Modular Decomposition for Large Language Model Compression
by: Lin, Chi-Heng, et al.
Published: (2024)

Pruning and Distilling Mixture-of-Experts into Dense Language Models
by: Kim, Junhyuck, et al.
Published: (2026)

Bilevel ZOFO: Efficient LLM Fine-Tuning and Meta-Training
by: Shirkavand, Reza, et al.
Published: (2025)

Auto-Train-Once: Controller Network Guided Automatic Network Pruning from Scratch
by: Wu, Xidong, et al.
Published: (2024)

MossNet: Mixture of State-Space Experts is a Multi-Head Attention
by: Tuli, Shikhar, et al.
Published: (2025)

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs
by: Lu, Lei, et al.
Published: (2024)

ARGUS: Hallucination and Omission Evaluation in Video-LLMs
by: Rawal, Ruchit, et al.
Published: (2025)

MoNE: Replacing Redundant Experts with Lightweight Novices for Structured Pruning of MoE
by: Zhang, Geng, et al.
Published: (2025)

MoST: Mixing Speech and Text with Modality-Aware Mixture of Experts
by: Lou, Yuxuan, et al.
Published: (2026)

BuddyMoE: Exploiting Expert Redundancy to Accelerate Memory-Constrained Mixture-of-Experts Inference
by: Wang, Yun, et al.
Published: (2025)

On the existence of positive solution for a Neumann problem with double critical exponents in half-space
by: Deng, Yinbin, et al.
Published: (2024)

$μ$-MoE: Test-Time Pruning as Micro-Grained Mixture-of-Experts
by: Koike-Akino, Toshiaki, et al.
Published: (2025)

Cluster-Driven Expert Pruning for Mixture-of-Experts Large Language Models
by: Guo, Hongcheng, et al.
Published: (2025)

ProbMoE: Differentiable Probabilistic Routing for Mixture-of-Experts
by: Zhao, Heng, et al.
Published: (2026)

Modeling Missing at Random Neuropsychological Test Scores Using a Mixture of Binomial Product Experts
by: Suen, Daniel, et al.
Published: (2023)

DiEP: Adaptive Mixture-of-Experts Compression through Differentiable Expert Pruning
by: Bai, Sikai, et al.
Published: (2025)

Sparse-Dense Mixture of Experts Adapter for Multi-Modal Tracking
by: Zhu, Yabin, et al.
Published: (2026)

MoE Jetpack: From Dense Checkpoints to Adaptive Mixture of Experts for Vision Tasks
by: Zhu, Xingkui, et al.
Published: (2024)

MoQE: Improve Quantization Model performance via Mixture of Quantization Experts
by: Zhang, Jinhao, et al.
Published: (2025)

Transformation-Augmented GRPO for Enhancing Exploration in Reasoning of Large Language Models
by: Le, Khiem, et al.
Published: (2026)

Investigating Mixture of Experts in Dense Retrieval
by: Sokli, Effrosyni, et al.
Published: (2024)

Catalog-Native LLM: Speaking Item-ID Dialect with Less Entanglement for Recommendation
by: Shirkavand, Reza, et al.
Published: (2025)

PreSiBOGNN: Multi‐Modal Graph Neural Network for Prediction of Cognitive Improvement in Medication Usage in UK Biobank
by: Dhawal Priyadarshi, et al.
Published: (2024)

MoE++: Accelerating Mixture-of-Experts Methods with Zero-Computation Experts
by: Jin, Peng, et al.
Published: (2024)

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation
by: Yang, Xiaomeng, et al.
Published: (2025)

Temporally Extended Mixture-of-Experts Models
by: Shen, Zeyu, et al.
Published: (2026)

Not All Experts are Equal: Efficient Expert Pruning and Skipping for Mixture-of-Experts Large Language Models
by: Lu, Xudong, et al.
Published: (2024)

MoE-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition
by: Yang, Cheng, et al.
Published: (2024)

LadderMoE: Ladder-Side Mixture of Experts Adapters for Bronze Inscription Recognition
by: Zhou, Rixin, et al.
Published: (2025)

MoBE: Mixture-of-Basis-Experts for Compressing MoE-based LLMs
by: Chen, Xiaodong, et al.
Published: (2025)