4 papers
Agentic Fusion of Large Atomic and Language Models to Accelerate Superconductor Discovery
Mingze Li, Yu Rong, Songyou Li +16
Artificial intelligence has accelerated materials discovery through high-throughput prediction and generation, yet the decision problem remains a formidable bottleneck. While curre…
RedParrot: Accelerating NL-to-DSL for Business Analytics via Query Semantic Caching
Tong Wang, Yongqin Xu, Jianfeng Zhang +6
Recently, at Xiaohongshu, the rapid expansion of e-commerce and advertising demands real-time business analytics with high accuracy and low latency. To meet this demand, systems ty…
Cognitive Chunking for Soft Prompts: Accelerating Compressor Learning via Block-wise Causal Masking
Guojie Liu, Yiqi Wang, Yanfeng Yang +4
Providing extensive context via prompting is vital for leveraging the capabilities of Large Language Models (LLMs). However, lengthy contexts significantly increase inference laten…
Stand on The Shoulders of Giants: Building JailExpert from Previous Attack Experience
Xi Wang, Songlei Jian, Shasha Li +9
Large language models (LLMs) generate human-aligned content under certain safety constraints. However, the current known technique ``jailbreak prompt'' can circumvent safety-aligne…