5 papers
From Static Inference to Dynamic Interaction: A Survey of Streaming Large Language Models
Junlong Tong, Zilong Wang, YuJie Ren +4
Standard Large Language Models (LLMs) are predominantly designed for static inference with pre-defined inputs, which limits their applicability in dynamic, real-time scenarios. To…
Detecting Hallucinations in Authentic LLM-Human Interactions
Yujie Ren, Niklas Gruhlke, Anne Lauscher
As large language models (LLMs) are increasingly applied in sensitive domains such as medicine and law, hallucination detection has become a critical task. Although numerous benchm…
LLaDA2.1: Speeding Up Text Diffusion via Token Editing
Tiwei Bie, Maosong Cao, Xiang Cao +47
While LLaDA2.0 showcased the scaling potential of 100B-level block-diffusion models and their inherent parallelization, the delicate equilibrium between decoding speed and generati…
Semantic Scheduling for LLM Inference
Wenyue Hua, Dujian Ding, Yile Gu +4
Conventional operating system scheduling algorithms are largely content-ignorant, making decisions based on factors such as latency or fairness without considering the actual inten…
From Commands to Prompts: LLM-based Semantic File System for AIOS
Zeru Shi, Kai Mei, Mingyu Jin +9
Large language models (LLMs) have demonstrated significant potential in the development of intelligent applications and systems such as LLM-based agents and agent operating systems…