1.1k citations
- Amazon (United States)US32 papers
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- Microsoft Research (United Kingdom)GB8 papers
- Google (United States)US7 papers
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387 papers
AGWM: Affordance-Grounded World Models for Environments with Compositional Prerequisites
Qinshi Zhang, Weipeng Deng, Zhihan Jiang +4
In model-based learning, the agent learns behaviors by simulating trajectories based on world model predictions. Standard world models typically learn a stationary transition funct…
EventADL: Open-Box Anomaly Detection and Localization Framework for Events in Cloud-Based Service Systems
Luan Pham, Victor Nicolet, Joey Dodds +2
Anomaly detection and localization (ADL) is critical for maintaining reliability and availability in cloud systems. Recent ADL developments focus on metric and log data, leaving ev…
Uncertainty Quantification in CNN Through the Bootstrap of Convex Neural Networks
Hongfei Du, Emre Barut, Fang Jin
Despite the popularity of Convolutional Neural Networks (CNN), the problem of uncertainty quantification (UQ) of CNN has been largely overlooked. Lack of efficient UQ tools severel…
An Agentic Multi-Agent Architecture for Cybersecurity Risk Management
Ravish Gupta, Saket Kumar, Shreeya Sharma +2
Getting a real cybersecurity risk assessment for a small organization is expensive -- a NIST CSF-aligned engagement runs $15,000 on the low end, takes weeks, and depends on practit…
Beyond Perfect APIs: A Comprehensive Evaluation of LLM Agents Under Real-World API Complexity
Doyoung Kim, Zhiwei Ren, Jie Hao +11
We introduce WildAGTEval, a benchmark designed to evaluate large language model (LLM) agents' function-calling capabilities under realistic API complexity. Unlike prior work that a…
CourtMotion: Learning Event-Driven Motion Representations from Skeletal Data for Basketball
Omer Sela, Michael Chertok, Lior Wolf
This paper presents CourtMotion, a spatiotemporal modeling framework for analyzing and predicting game events and plays as they develop in professional basketball. Anticipating bas…