Summary of Gptvq: the Blessing Of Dimensionality For Llm Quantization, by Mart Van Baalen et al.
GPTVQ: The Blessing of Dimensionality for LLM Quantizationby Mart van Baalen, Andrey Kuzmin, Markus Nagel,…
Summary of Aptq: Attention-aware Post-training Mixed-precision Quantization For Large Language Models, by Ziyi Guan et al.
APTQ: Attention-aware Post-Training Mixed-Precision Quantization for Large Language Modelsby Ziyi Guan, Hantao Huang, Yupeng Su,…
Summary of Distillation Contrastive Decoding: Improving Llms Reasoning with Contrastive Decoding and Distillation, by Phuc Phan et al.
Distillation Contrastive Decoding: Improving LLMs Reasoning with Contrastive Decoding and Distillationby Phuc Phan, Hieu Tran,…
Summary of Text Me the Data: Generating Ground Pressure Sequence From Textual Descriptions For Har, by Lala Shakti Swarup Ray et al.
Text me the data: Generating Ground Pressure Sequence from Textual Descriptions for HARby Lala Shakti…
Summary of Towards a Tailored Mixed-precision Sub-8-bit Quantization Scheme For Gated Recurrent Units Using Genetic Algorithms, by Riccardo Miccini et al.
Towards a tailored mixed-precision sub-8-bit quantization scheme for Gated Recurrent Units using Genetic Algorithmsby Riccardo…
Summary of Db-llm: Accurate Dual-binarization For Efficient Llms, by Hong Chen et al.
DB-LLM: Accurate Dual-Binarization for Efficient LLMsby Hong Chen, Chengtao Lv, Liang Ding, Haotong Qin, Xiabin…
Summary of Wkvquant: Quantizing Weight and Key/value Cache For Large Language Models Gains More, by Yuxuan Yue et al.
WKVQuant: Quantizing Weight and Key/Value Cache for Large Language Models Gains Moreby Yuxuan Yue, Zhihang…
Summary of Edgeqat: Entropy and Distribution Guided Quantization-aware Training For the Acceleration Of Lightweight Llms on the Edge, by Xuan Shen et al.
EdgeQAT: Entropy and Distribution Guided Quantization-Aware Training for the Acceleration of Lightweight LLMs on the…
Summary of Any-precision Llm: Low-cost Deployment Of Multiple, Different-sized Llms, by Yeonhong Park et al.
Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMsby Yeonhong Park, Jake Hyun, SangLyul Cho, Bonggeun…
Summary of Prise: Llm-style Sequence Compression For Learning Temporal Action Abstractions in Control, by Ruijie Zheng et al.
PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Controlby Ruijie Zheng, Ching-An Cheng,…