9 papers
Token-Operations-Oriented Inference Optimization Techniques for Large Models
Shiguo Lian, Kai Wang, Zhaoxiang Liu +23
Large model inference optimization serves as a key foundation for supporting the scalable, low-cost, and highly stable operation of large model services. Centered on token-oriented…
GLM-5 Serving Parameter Tuning for OpenClaw: Single-Deployment MaaS Inference Optimization for Long-Context Agent Workloads
Minjie Hua, Ning Wang, Peijun Yang +2
OpenClaw requests are dominated by long, tool-augmented prefixes, including system prompts, conversation history, and tool outputs fed back into the context window. For this worklo…
Quantifying the Capability Boundary of DeepSeek Models: An Application-Driven Performance Analysis
Kaikai Zhao, Zhaoxiang Liu, Xuejiao Lei +12
DeepSeek-R1, known for its low training cost and exceptional reasoning capabilities, has achieved state-of-the-art performance on various benchmarks. However, detailed evaluations…
Safety Evaluation of DeepSeek Models in Chinese Contexts
Wenjing Zhang, Xuejiao Lei, Zhaoxiang Liu +8
Recently, the DeepSeek series of models, leveraging their exceptional reasoning capabilities and open-source strategy, is reshaping the global AI landscape. Despite these advantage…
Application-Driven AI Paradigm for Person Counting in Various Scenarios
Minjie Hua, Yibing Nan, Shiguo Lian
Person counting is considered as a fundamental task in video surveillance. However, the scenario diversity in practical applications makes it difficult to exploit a single person c…
Small Obstacle Avoidance Based on RGB-D Semantic Segmentation
Minjie Hua, Yibing Nan, Shiguo Lian
This paper presents a novel obstacle avoidance system for road robots equipped with RGB-D sensor that captures scenes of its way forward. The purpose of the system is to have road…