Winning the Pruning Gamble: A Unified Approach to Joint Sample and Token Pruning for Efficient Supervised Fine-Tuning
Fuente:
arXiv
Guardado en:
| Autores principales: | Wang, Shaobo, Wang, Jiaming, Zhang, Jiajun, Wang, Cong, Min, Yue, Wen, Zichen, Ren, Xingzhang, Huang, Fei, Jiang, Huiqiang, Lin, Junyang, Liu, Dayiheng, Zhang, Linfeng |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
UNSEEN: Enhancing Dataset Pruning from a Generalization Perspective
por: Xu, Furui, et al.
Publicado: (2025)
por: Xu, Furui, et al.
Publicado: (2025)
DISA: Offline Importance Sampling for Distribution-Matching LLM-RL
por: Wang, Shaobo, et al.
Publicado: (2026)
por: Wang, Shaobo, et al.
Publicado: (2026)
The Missing Piece in Pre-trained Model Evaluation: Reward-Guided Decoding Unlocks Task-Oriented Behavior Without Parameter Updates
por: Wang, Shaobo, et al.
Publicado: (2026)
por: Wang, Shaobo, et al.
Publicado: (2026)
Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?
por: Wen, Zichen, et al.
Publicado: (2025)
por: Wen, Zichen, et al.
Publicado: (2025)
Reasoning Like an Economist: Post-Training on Economic Problems Induces Strategic Generalization in LLMs
por: Zhou, Yufa, et al.
Publicado: (2025)
por: Zhou, Yufa, et al.
Publicado: (2025)
D2Pruner: Debiased Importance and Structural Diversity for MLLM Token Pruning
por: Zhang, Evelyn, et al.
Publicado: (2025)
por: Zhang, Evelyn, et al.
Publicado: (2025)
Rethinking LLM Evaluation: Can We Evaluate LLMs with 200x Less Data?
por: Wang, Shaobo, et al.
Publicado: (2025)
por: Wang, Shaobo, et al.
Publicado: (2025)
Comb, Prune, Distill: Towards Unified Pruning for Vision Model Compression
por: Schmitt, Jonas, et al.
Publicado: (2024)
por: Schmitt, Jonas, et al.
Publicado: (2024)
ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving
por: Sha, Lin, et al.
Publicado: (2026)
por: Sha, Lin, et al.
Publicado: (2026)
Data Whisperer: Efficient Data Selection for Task-Specific LLM Fine-Tuning via Few-Shot In-Context Learning
por: Wang, Shaobo, et al.
Publicado: (2025)
por: Wang, Shaobo, et al.
Publicado: (2025)
Beyond Text-Visual Attention: Exploiting Visual Cues for Effective Token Pruning in VLMs
por: Zhang, Qizhe, et al.
Publicado: (2024)
por: Zhang, Qizhe, et al.
Publicado: (2024)
PRANCE: Joint Token-Optimization and Structural Channel-Pruning for Adaptive ViT Inference
por: Li, Ye, et al.
Publicado: (2024)
por: Li, Ye, et al.
Publicado: (2024)
UTPTrack: Towards Simple and Unified Token Pruning for Visual Tracking
por: Wu, Hao, et al.
Publicado: (2026)
por: Wu, Hao, et al.
Publicado: (2026)
Towards Joint Quantization and Token Pruning of Vision-Language Models
por: Li, Xinqing, et al.
Publicado: (2026)
por: Li, Xinqing, et al.
Publicado: (2026)
OPUS: Towards Efficient and Principled Data Selection in Large Language Model Pre-training in Every Iteration
por: Wang, Shaobo, et al.
Publicado: (2026)
por: Wang, Shaobo, et al.
Publicado: (2026)
SP-VLA: A Joint Model Scheduling and Token Pruning Approach for VLA Model Acceleration
por: Li, Ye, et al.
Publicado: (2025)
por: Li, Ye, et al.
Publicado: (2025)
TransPrune: Token Transition Pruning for Efficient Large Vision-Language Model
por: Li, Ao, et al.
Publicado: (2025)
por: Li, Ao, et al.
Publicado: (2025)
LeanK: Learnable K Cache Channel Pruning for Efficient Decoding
por: Zhang, Yike, et al.
Publicado: (2025)
por: Zhang, Yike, et al.
Publicado: (2025)
Stop Looking for Important Tokens in Multimodal Language Models: Duplication Matters More
por: Wen, Zichen, et al.
Publicado: (2025)
por: Wen, Zichen, et al.
Publicado: (2025)
Fast Track to Winning Tickets: Repowering One-Shot Pruning for Graph Neural Networks
por: Yue, Yanwei, et al.
Publicado: (2024)
por: Yue, Yanwei, et al.
Publicado: (2024)
Fast SAM2 with Text-Driven Token Pruning
por: Mandal, Avilasha, et al.
Publicado: (2025)
por: Mandal, Avilasha, et al.
Publicado: (2025)
CLOVER: Cross-Layer Orthogonal Vectors Pruning and Fine-Tuning
por: Meng, Fanxu, et al.
Publicado: (2024)
por: Meng, Fanxu, et al.
Publicado: (2024)
Diffusion LLM with Native Variable Generation Lengths: Let [EOS] Lead the Way
por: Yang, Yicun, et al.
Publicado: (2025)
por: Yang, Yicun, et al.
Publicado: (2025)
SpeechPrune: Context-aware Token Pruning for Speech Information Retrieval
por: Lin, Yueqian, et al.
Publicado: (2024)
por: Lin, Yueqian, et al.
Publicado: (2024)
Pruning for Protection: Increasing Jailbreak Resistance in Aligned LLMs Without Fine-Tuning
por: Hasan, Adib, et al.
Publicado: (2024)
por: Hasan, Adib, et al.
Publicado: (2024)
Token Pruning for Caching Better: 9 Times Acceleration on Stable Diffusion for Free
por: Zhang, Evelyn, et al.
Publicado: (2024)
por: Zhang, Evelyn, et al.
Publicado: (2024)
An Empirical Study of Parameter Efficient Fine-tuning on Vision-Language Pre-train Model
por: Tian, Yuxin, et al.
Publicado: (2024)
por: Tian, Yuxin, et al.
Publicado: (2024)
GridPrune: From "Where to Look" to "What to Select" in Visual Token Pruning for MLLMs
por: Duan, Yuxiang, et al.
Publicado: (2025)
por: Duan, Yuxiang, et al.
Publicado: (2025)
HiPrune: Hierarchical Attention for Efficient Token Pruning in Vision-Language Models
por: Liu, Jizhihui, et al.
Publicado: (2025)
por: Liu, Jizhihui, et al.
Publicado: (2025)
DivPrune: Diversity-based Visual Token Pruning for Large Multimodal Models
por: Alvar, Saeed Ranjbar, et al.
Publicado: (2025)
por: Alvar, Saeed Ranjbar, et al.
Publicado: (2025)
Compute Only 16 Tokens in One Timestep: Accelerating Diffusion Transformers with Cluster-Driven Feature Caching
por: Zheng, Zhixin, et al.
Publicado: (2025)
por: Zheng, Zhixin, et al.
Publicado: (2025)
SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning
por: Wang, Hanrui, et al.
Publicado: (2020)
por: Wang, Hanrui, et al.
Publicado: (2020)
Light-PEFT: Lightening Parameter-Efficient Fine-Tuning via Early Pruning
por: Gu, Naibin, et al.
Publicado: (2024)
por: Gu, Naibin, et al.
Publicado: (2024)
Effective Fine-Tuning with Eigenvector Centrality Based Pruning
por: Chowdhury, Shaif, et al.
Publicado: (2025)
por: Chowdhury, Shaif, et al.
Publicado: (2025)
Prune, Don't Rebuild: Efficiently Tuning $α$-Reachable Graphs for Nearest Neighbor Search
por: Zhang, Tian, et al.
Publicado: (2026)
por: Zhang, Tian, et al.
Publicado: (2026)
Layer Pruning with Consensus: A Triple-Win Solution
por: Mugnaini, Leandro Giusti, et al.
Publicado: (2024)
por: Mugnaini, Leandro Giusti, et al.
Publicado: (2024)
Sink-Token-Aware Pruning for Fine-Grained Video Understanding in Efficient Video LLMs
por: Kim, Kibum, et al.
Publicado: (2026)
por: Kim, Kibum, et al.
Publicado: (2026)
GradPruner: Gradient-Guided Layer Pruning Enabling Efficient Fine-Tuning and Inference for LLMs
por: Huang, Wei, et al.
Publicado: (2026)
por: Huang, Wei, et al.
Publicado: (2026)
Flash-Unified: A Training-Free and Task-Aware Acceleration Framework for Native Unified Models
por: Ke, Junlong, et al.
Publicado: (2026)
por: Ke, Junlong, et al.
Publicado: (2026)
PAT: Pruning-Aware Tuning for Large Language Models
por: Liu, Yijiang, et al.
Publicado: (2024)
por: Liu, Yijiang, et al.
Publicado: (2024)
Ejemplares similares
-
UNSEEN: Enhancing Dataset Pruning from a Generalization Perspective
por: Xu, Furui, et al.
Publicado: (2025) -
DISA: Offline Importance Sampling for Distribution-Matching LLM-RL
por: Wang, Shaobo, et al.
Publicado: (2026) -
The Missing Piece in Pre-trained Model Evaluation: Reward-Guided Decoding Unlocks Task-Oriented Behavior Without Parameter Updates
por: Wang, Shaobo, et al.
Publicado: (2026) -
Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?
por: Wen, Zichen, et al.
Publicado: (2025) -
Reasoning Like an Economist: Post-Training on Economic Problems Induces Strategic Generalization in LLMs
por: Zhou, Yufa, et al.
Publicado: (2025)