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cs.CL2025

XQuant: Achieving Ultra-Low Bit KV Cache Quantization with Cross-Layer Compression

Haoqi Yang, Yao Yao, Zuchao Li +3

Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse natural language processing tasks. However, their extensive memory requirements, particularly…

cs.CL2024

Reference Trustable Decoding: A Training-Free Augmentation Paradigm for Large Language Models

Luohe Shi, Yao Yao, Zuchao Li +2

Large language models (LLMs) have rapidly advanced and demonstrated impressive capabilities. In-Context Learning (ICL) and Parameter-Efficient Fine-Tuning (PEFT) are currently two…

cs.CL2024

Keep the Cost Down: A Review on Methods to Optimize LLM' s KV-Cache Consumption

Luohe Shi, Hongyi Zhang, Yao Yao +2

Large Language Models (LLMs), epitomized by ChatGPT's release in late 2022, have revolutionized various industries with their advanced language comprehension. However, their effici…

cs.CL2024

GKT: A Novel Guidance-Based Knowledge Transfer Framework For Efficient Cloud-edge Collaboration LLM Deployment

Yao Yao, Zuchao Li, Hai Zhao

The burgeoning size of Large Language Models (LLMs) has led to enhanced capabilities in generating responses, albeit at the expense of increased inference times and elevated resour…

cs.CL2024

SirLLM: Streaming Infinite Retentive LLM

Yao Yao, Zuchao Li, Hai Zhao

As Large Language Models (LLMs) become increasingly prevalent in various domains, their ability to process inputs of any length and maintain a degree of memory becomes essential. H…

cs.CL2024

Beyond Chain-of-Thought, Effective Graph-of-Thought Reasoning in Language Models

Yao Yao, Zuchao Li, Hai Zhao

With the widespread use of language models (LMs) in NLP tasks, researchers have discovered the potential of Chain-of-thought (CoT) to assist LMs in accomplishing complex reasoning…