· ai
[Paper] Trusted AI Agents in the Cloud
AI agents powered by large language models are increasingly deployed as cloud services that autonomously access sensitive data, invoke external tools, and inter...
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- · ai
[Paper] Impugan: Learning Conditional Generative Models for Robust Data Imputation
Incomplete data are common in real-world applications. Sensors fail, records are inconsistent, and datasets collected from different sources often differ in sca...
- · ai
[Paper] Developing synthetic microdata through machine learning for firm-level business surveys
Public-use microdata samples (PUMS) from the United States (US) Census Bureau on individuals have been available for decades. However, large increases in comput...
- · ai
[Paper] Variational Quantum Rainbow Deep Q-Network for Optimizing Resource Allocation Problem
Resource allocation remains NP-hard due to combinatorial complexity. While deep reinforcement learning (DRL) methods, such as the Rainbow Deep Q-Network (DQN), ...
- · ai
[Paper] Zoom in, Click out: Unlocking and Evaluating the Potential of Zooming for GUI Grounding
Grounding is a fundamental capability for building graphical user interface (GUI) agents. Although existing approaches rely on large-scale bounding box supervis...
- · ai
[Paper] Designing an Optimal Sensor Network via Minimizing Information Loss
Optimal experimental design is a classic topic in statistics, with many well-studied problems, applications, and solutions. The design problem we study is the p...
- · ai
[Paper] Measuring the Effect of Background on Classification and Feature Importance in Deep Learning for AV Perception
Common approaches to explainable AI (XAI) for deep learning focus on analyzing the importance of input features on the classification task in a given model: sal...
- · ai
[Paper] Synset Signset Germany: a Synthetic Dataset for German Traffic Sign Recognition
In this paper, we present a synthesis pipeline and dataset for training / testing data in the task of traffic sign recognition that combines the advantages of d...
- · ai
[Paper] Physically-Based Simulation of Automotive LiDAR
We present an analytic model for simulating automotive time-of-flight (ToF) LiDAR that includes blooming, echo pulse width, and ambient light, along with steps ...
- · ai
[Paper] On the Bayes Inconsistency of Disagreement Discrepancy Surrogates
Deep neural networks often fail when deployed in real-world contexts due to distribution shift, a critical barrier to building safe and reliable systems. An eme...
- · ai
[Paper] A Comparative Study on Synthetic Facial Data Generation Techniques for Face Recognition
Facial recognition has become a widely used method for authentication and identification, with applications for secure access and locating missing persons. Its ...
- · ai
[Paper] World Models That Know When They Don't Know: Controllable Video Generation with Calibrated Uncertainty
Recent advances in generative video models have led to significant breakthroughs in high-fidelity video synthesis, specifically in controllable video generation...