Poster "training-free optimization" Papers

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DyMU: Dynamic Merging and Virtual Unmerging for Efficient Variable-Length VLMs

Zhenhailong Wang, Senthil Purushwalkam, Caiming Xiong et al.

EasySpec: Layer-Parallel Speculative Decoding for Efficient Multi-GPU Utilization

Yize Wu, KE GAO, Ling Li et al.

NEURIPS 2025arXiv:2502.02493

ShortV: Efficient Multimodal Large Language Models by Freezing Visual Tokens in Ineffective Layers

Qianhao Yuan, Qingyu Zhang, yanjiang liu et al.

ICCV 2025arXiv:2504.00502

Training-Free Bayesianization for Low-Rank Adapters of Large Language Models

Haizhou Shi, Yibin Wang, Ligong Han et al.

NEURIPS 2025arXiv:2412.05723

DeepCache: Accelerating Diffusion Models for Free

Xinyin Ma, Gongfan Fang, Xinchao Wang

CVPR 2024arXiv:2312.00858

Move Anything with Layered Scene Diffusion

Jiawei Ren, Mengmeng Xu, Jui-Chieh Wu et al.

CVPR 2024arXiv:2404.07178

Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration

Zhongzhi Yu, Zheng Wang, Yonggan Fu et al.

ICML 2024arXiv:2406.15765