35 citations · 61 across the 8 of their papers we have counts for
4 papers · 1 filter
KnowSim: Evaluating Information Calibration in LLM Assistants with User Simulators that Learn
Yoonjoo Lee, Hyoungwook Jin, Tae Soo Kim +3
To effectively collaborate with users on knowledge-intensive tasks, Large Language Models (LLMs) must perform information calibration: matching content to a user's evolving underst…
Mandol: An Agglomerative Agent Memory System for Long-Term Conversations
Yuhan Zhang, Zhiyuan Guo, Ziheng Zeng +3
Long-term conversational agents need to remember and query cross-session, multi-typed information with complex correlations. Existing agent memory systems rely on heterogeneous vec…
Heterogeneous Computing: The Key to Powering the Future of AI Agent Inference
Yiren Zhao, Junyi Liu
AI agent inference is driving an inference heavy datacenter future and exposes bottlenecks beyond compute - especially memory capacity, memory bandwidth and high-speed interconnect…
UTune: Towards Uncertainty-Aware Online Index Tuning
Chenning Wu, Sifan Chen, Wentao Wu +4
There have been a flurry of recent proposals on learned benefit estimators for index tuning. Although these learned estimators show promising improvement over what-if query optimiz…