Approximate nearest neighbor search (ANNS) over billion-scale vector datasets has become a foundational operator for modern retrieval systems, powering large-scale recommendation, semantic search, and LLM/RAG workloads. Although GPUs offer massive parallelism and high-bandwidth memory for batched vector search, their l...
Yue-Meng Xu, Zongxi Liu, Junyu Long et al.· 0 citations
Vertumnus is presented, an adaptive CP serving system designed for heterogeneous and evolving workloads that reduces mean TTFT and improves token-weighted SLO attainment and introduces a global prefix-cache management policy that coordinates cache placement and replication among workers with the same or different CP de...
Jiarui Guo, Rong-Le Wang, Pei-Jun Huang et al.· 0 citations
Real-Q (Real-time E2E-loss Aligned LLM Quantization), a novel PTQ paradigm that breaks this compromise: instead of diluting the objective for the sake of analytic tractability, REAL-Q targets an end-to-end-aligned surrogate of the global loss and refines it via fine-grained, dynamic Block-wise Gradient Descent applied...
Qian Zhang, Yao-Ming Li, Zheng Tan et al.· 0 citations
RealClawBench is introduced, a live benchmark framework built from real OpenClaw sessions to capture the distribution, diversity, and real-world difficulty of deployed agent use and provides a practical path toward benchmarks that better measure agent capability in actual use.
Zongwei Lv, Zhewen Tan, Yao-Ming Li et al.· arXiv.org· 1 citation· ⚡1
This work introduces ArborMem, an online memory framework that represents a long-running conversation as a navigable forest of interaction states that outperforms the strongest baselines on three established benchmarks and introduces BranchMemEval, a controlled diagnostic benchmark for interleaved and resumable interac...
Zongwei Lv, Yue-Meng Xu, Yilun Yao et al.· 0 citations
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