6 papers
MoQAE: Mixed-Precision Quantization for Long-Context LLM Inference via Mixture of Quantization-Aware Experts
Wei Tao, Haocheng Lu, Xiaoyang Qu +4
One of the primary challenges in optimizing large language models (LLMs) for long-context inference lies in the high memory consumption of the Key-Value (KV) cache. Existing approa…
RATE-Nav: Region-Aware Termination Enhancement for Zero-shot Object Navigation with Vision-Language Models
Junjie Li, Nan Zhang, Xiaoyang Qu +4
Object Navigation (ObjectNav) is a fundamental task in embodied artificial intelligence. Although significant progress has been made in semantic map construction and target directi…
BAGNet: A Boundary-Aware Graph Attention Network for 3D Point Cloud Semantic Segmentation
Wei Tao, Xiaoyang Qu, Kai Lu +3
Since the point cloud data is inherently irregular and unstructured, point cloud semantic segmentation has always been a challenging task. The graph-based method attempts to model…
MADLLM: Multivariate Anomaly Detection via Pre-trained LLMs
Wei Tao, Xiaoyang Qu, Kai Lu +3
When applying pre-trained large language models (LLMs) to address anomaly detection tasks, the multivariate time series (MTS) modality of anomaly detection does not align with the…
RUNA: Object-level Out-of-Distribution Detection via Regional Uncertainty Alignment of Multimodal Representations
Bin Zhang, Jinggang Chen, Xiaoyang Qu +5
Enabling object detectors to recognize out-of-distribution (OOD) objects is vital for building reliable systems. A primary obstacle stems from the fact that models frequently do no…
Hammer: Towards Efficient Hot-Cold Data Identification via Online Learning
Kai Lu, Siqi Zhao, Jiguang Wan
Efficient management of storage resources in big data and cloud computing environments requires accurate identification of data's "cold" and "hot" states. Traditional methods, such…