4 citations · 5 across the 25 of their papers we have counts for
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cs.CL2026
SAES-SVD: Self-Adaptive Suppression of Accumulated and Local Errors for SVD-based LLM Compression
Xing Hu, Dawei Yang, Yuan Cheng +2
The rapid growth in the parameter scale of large language models (LLMs) has created a high demand for efficient compression techniques. As a hardware-agnostic and highly compatible…
cs.CL2025
DLLMQuant: Quantizing Diffusion-based Large Language Models
Chen Xu, Dawei Yang
Diffusion-based large language models (DLLMs) have shown promise for non-autoregressive text generation, but their deployment is constrained by large model sizes and heavy computat…
cs.CL2023★ 4 cited
ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models
Zhihang Yuan, Yuzhang Shang, Yue Song +4
In this paper, we introduce a new post-training compression paradigm for Large Language Models (LLMs) to facilitate their wider adoption. We delve into LLM weight low-rank decompos…