2 papers
cs.CR2026
Rethinking Latency Denial-of-Service: Attacking the LLM Serving Framework, Not the Model
Tianyi Wang, Huawei Fan, Yuanchao Shu +2
LLM inference is inherently expensive, even a modest slowdown can translate into substantial operating costs and severe availability risks. Recently, a growing body of research kno…
cs.RO2025
RoboInspector: Unveiling the Unreliability of Policy Code for LLM-enabled Robotic Manipulation
Chenduo Ying, Linkang Du, Peng Cheng +1
Large language models (LLMs) demonstrate remarkable capabilities in reasoning and code generation, enabling robotic manipulation to be initiated with just a single instruction. The…