1 citations · 1 across the 3 of their papers we have counts for
5 papers
Embodied.cpp: A Portable Inference Runtime of Embodied AI Models on Heterogeneous Robots
Ling Xu, Chuyu Han, Borui Li +8
Embodied AI models now span vision-language-action (VLA) models and world-action models (WAMs), but practical deployment remains fragmented across model-specific Python stacks, bac…
OxyGen: Unified KV Cache Management for VLA Inference under Multi-Task Parallelism
Xiangyu Li, Huaizhi Tang, Xin Ding +3
Embodied AI agents increasingly require parallel execution of multiple tasks, such as manipulation, conversation, and memory construction, from shared observations under distinct t…
Vec-LUT: Vector Table Lookup for Parallel Ultra-Low-Bit LLM Inference on Edge Devices
Xiangyu Li, Chengyu Yin, Weijun Wang +3
Large language models (LLMs) are increasingly deployed on edge devices. To meet strict resource constraints, real-world deployment has pushed LLM quantization from 8-bit to 4-bit,…
An Empirical Study of LLM Reasoning Ability Under Strict Output Length Constraint
Yi Sun, Han Wang, Jiaqiang Li +8
Recent work has demonstrated the remarkable potential of Large Language Models (LLMs) in test-time scaling. By making models think before answering, they are able to achieve much h…
ChainStream: An LLM-based Framework for Unified Synthetic Sensing
Jiacheng Liu, Yuanchun Li, Liangyan Li +5
Many applications demand context sensing to offer personalized and timely services. Yet, developing sensing programs can be challenging for developers and using them is privacy-con…