6 papers
MatrAIx: Simulating the World with 8.3 Billion Persona Agents
Xiaomin Li, Yuexing Hao, Jianheng Hou +90
Human evaluation of AI systems and digital products is costly, slow, and difficult to scale. Offline evaluations are more scalable but often abstract away human diversity and inter…
Quantifying Trust: Financial Risk Management for Trustworthy AI Agents
Wenyue Hua, Tianyi Peng, Chi Wang +4
Prior work on trustworthy AI emphasizes model-internal properties such as bias mitigation, adversarial robustness, and interpretability. As AI systems evolve into autonomous agents…
AgentOpt v0.1 Technical Report: Client-Side Optimization for LLM-Based Agent
Wenyue Hua, Sripad Karne, Qian Xie +4
AI agents are increasingly deployed in real-world applications, including systems such as Manus, OpenClaw, and coding agents. Existing research has primarily focused on server-side…
VineLM: Trie-Based Fine-Grained Control for Agentic Workflows
Nikos Pagonas, Matthew Lou, Tianyi Peng +2
Agentic workflows interleave configurable LLM stages with tool stages and often include retries or refinement loops. Existing workflow managers profile full workflow configurations…
Tail-Optimized Caching for LLM Inference
Wenxin Zhang, Yueying Li, Ciamac C. Moallemi +1
Prompt caching is critical for reducing latency and cost in LLM inference: OpenAI and Anthropic report up to 50-90% cost savings through prompt reuse. Despite its widespread succes…
Throughput-Optimal Scheduling Algorithms for LLM Inference and AI Agents
J. G. Dai, Tianze Deng, Yueying Li +1
As demand for Large Language Models (LLMs) and AI agents grows rapidly, optimizing systems for efficient LLM inference becomes critical. While significant efforts have targeted sys…