Qi Gu

The paper introduces LinuxArena, a large-scale, diverse control setting for testing AI agents in live production environments, demonstrating its utility for evaluating both attack and defense mechanisms.

The paper introduces MIRAGE, a novel pipeline that generates context-aware prompt injection attacks by injecting malicious text into user-generated content regions of mobile screenshots, successfully demonstrating the vulnerability of current GUI agents.

The paper introduces MIRAGE, a novel pipeline that generates context-aware prompt injection attacks by embedding malicious text into user-generated content regions of mobile screenshots, successfully demonstrating the vulnerability of current VLM-driven GUI agents.

KairosAgent is a novel agentic framework that combines Large Language Models (LLMs) for semantic reasoning and Time Series Foundation Models (TSFMs) for numerical forecasting, achieving superior multimodal time series prediction.

The paper introduces SURE, a unified framework designed to standardize and improve the comparability and reproducibility of evaluations for advanced speech understanding models.

The paper introduces MineExplorer, a new benchmark in Minecraft, to evaluate the sustained open-world exploration capabilities of MLLM agents, finding that long-horizon coordination remains a significant challenge.

The paper introduces 3DCodeBench, a systematic benchmark and platform for evaluating Vision-Language Model (VLM) agents' ability to generate procedural 3D models from text and images using code.

The paper proposes Skill-RM, a unified framework that treats reward modeling as an agentic task to consistently integrate diverse evaluation criteria, achieving superior performance over traditional methods.

The paper proposes a novel Bayesian framework to learn the optimal decision strategy for the stochastic shortest path problem by directly constructing the posterior beliefs for the action-value function $Q^*$ using Bellman's optimality equations.