5 papers
Neuro-Symbolic Verification on Instruction Following of LLMs
Yiming Su, Kunzhao Xu, Yanjie Gao +4
A fundamental problem of applying Large Language Models (LLMs) to important applications is that LLMs do not always follow instructions, and violations are often hard to observe or…
FFTrainer: Fast Failover in Large-Language Model Training with Almost-Free State Management
Bohan Zhao, Yuanhong Wang, Chenglin Liu +6
Recent developments in large language models (LLMs) have introduced new requirements for efficient and robust training. As LLM clusters scale, node failures, lengthy recoveries, an…
LoopLLM: Transferable Energy-Latency Attacks in LLMs via Repetitive Generation
Xingyu Li, Xiaolei Liu, Cheng Liu +4
As large language models (LLMs) scale, their inference incurs substantial computational resources, exposing them to energy-latency attacks, where crafted prompts induce high energy…
From Large to Small: Transferring CUDA Optimization Expertise via Reasoning Graph
Junfeng Gong, Zhiyi Wei, Junying Chen +2
Despite significant evolution of CUDA programming and domain-specific libraries, effectively utilizing GPUs with massively parallel engines remains difficult. Large language models…
Large Processor Chip Model
Kaiyan Chang, Mingzhi Chen, Yunji Chen +40
Computer System Architecture serves as a crucial bridge between software applications and the underlying hardware, encompassing components like compilers, CPUs, coprocessors, and R…