3 papers
cs.CL2025
From 128K to 4M: Efficient Training of Ultra-Long Context Large Language Models
Chejian Xu, Wei Ping, Peng Xu +5
Long-context capabilities are essential for a wide range of applications, including document and video understanding, in-context learning, and inference-time scaling, all of which…
cs.CR2023
Identifying and Mitigating Vulnerabilities in LLM-Integrated Applications
Fengqing Jiang, Zhangchen Xu, Luyao Niu +4
Large language models (LLMs) are increasingly deployed as the service backend for LLM-integrated applications such as code completion and AI-powered search. LLM-integrated applicat…
cs.CL2023
InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining
Boxin Wang, Wei Ping, Lawrence McAfee +4
Pretraining auto-regressive large language models~(LLMs) with retrieval demonstrates better perplexity and factual accuracy by leveraging external databases. However, the size of e…