3 papers
cs.DC2025
P/D-Device: Disaggregated Large Language Model between Cloud and Devices
Yibo Jin, Yixu Xu, Yue Chen +27
Serving disaggregated large language models has been widely adopted in industrial practice for enhanced performance. However, too many tokens generated in decoding phase, i.e., occ…
cs.CL2025
ProBench: Benchmarking Large Language Models in Competitive Programming
Lei Yang, Renren Jin, Ling Shi +3
With reasoning language models such as OpenAI-o3 and DeepSeek-R1 emerging, large language models (LLMs) have entered a new phase of development. However, existing benchmarks for co…
cs.CL2025
TrustRAG: Enhancing Robustness and Trustworthiness in Retrieval-Augmented Generation
Huichi Zhou, Kin-Hei Lee, Zhonghao Zhan +5
Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by integrating external knowledge sources, enabling more accurate and contextually relevant responses tai…