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20242026
most citedA Survey on Efficient Inference for Large Language Models

23 citations · 23 across the 10 of their papers we have counts for

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6 papers · 1 filter

cs.CL2025

VocabTailor: Dynamic Vocabulary Selection for Downstream Tasks in Small Language Models

Hanling Zhang, Yayu Zhou, Tongcheng Fang +4

Small Language Models (SLMs) provide computational advantages in resource-constrained environments, yet memory limitations remain a critical bottleneck for edge device deployment.…

cs.LG2025

Spec-VLA: Speculative Decoding for Vision-Language-Action Models with Relaxed Acceptance

Songsheng Wang, Rucheng Yu, Zhihang Yuan +4

Vision-Language-Action (VLA) models have made substantial progress by leveraging the robust capabilities of Visual Language Models (VLMs). However, VLMs' significant parameter size…

cs.CL2025

R2R: Efficiently Navigating Divergent Reasoning Paths with Small-Large Model Token Routing

Tianyu Fu, Yi Ge, Yichen You +6

Large Language Models (LLMs) achieve impressive reasoning capabilities at the cost of substantial inference overhead, posing substantial deployment challenges. Although distilled S…

cs.CV2025

VGDFR: Diffusion-based Video Generation with Dynamic Latent Frame Rate

Zhihang Yuan, Rui Xie, Yuzhang Shang +5

Diffusion Transformer(DiT)-based generation models have achieved remarkable success in video generation. However, their inherent computational demands pose significant efficiency c…

cs.CV2025

DLFR-VAE: Dynamic Latent Frame Rate VAE for Video Generation

Zhihang Yuan, Siyuan Wang, Rui Xie +6

In this paper, we propose the Dynamic Latent Frame Rate VAE (DLFR-VAE), a training-free paradigm that can make use of adaptive temporal compression in latent space. While existing…

cs.CV2025

DiTFastAttnV2: Head-wise Attention Compression for Multi-Modality Diffusion Transformers

Hanling Zhang, Rundong Su, Zhihang Yuan +5

Text-to-image generation models, especially Multimodal Diffusion Transformers (MMDiT), have shown remarkable progress in generating high-quality images. However, these models often…