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X-AgentRed: Red-Teaming Personal Agents in Evolving Multi-Service Ecosystems
Personal agents connect to services across the web and applications through tools. As accumulated effects interact across services, unintended or harmful outcomes can arise when agents fulfill benign user requests. Proactively ide...
Prediction Is Not a Sufficient Memory State
A memory that reproduces every current prediction may still have forgotten how to learn from the next observation. We characterize this distinction for exact cumulative learning and attention. For smooth convex residual losses wit...
BT-Agent: Deploying Onboard Robot Agents with Behavior Trees and Multi-Fidelity Evaluation
Deploying language-model agents onboard mobile robots requires task reasoning and responsive execution within limited compute and memory. Standard ReAct loops can stall when a proposed action encounters an unexpected state, becaus...
Decision-Focused Learning for Cyber-Physical Risk-Aware Power Grid Operations
Power grid cyber-physical security requires intrusion detection methods that account for the operational consequences of detection errors. Existing intrusion detection approaches primarily focus on the predictive performance of le...
Inference-Time Steering Across Scaffolds and Epitopes for Sample-Efficient De Novo Nanobody Design
Generative molecular design typically relies on over-generation and post-hoc filtering. Inference-time steering methods like Feynman-Kac (FK) steering improve efficiency by biasing trajectories toward high-reward candidates, yet t...
Specialists Learn Faster: Knowledge Organization in Pre-training Shapes Knowledge Update Efficiency
Language models must continually update their knowledge to remain current. Most existing work focuses on making these post-training updates efficient, but this paper investigates a more foundational question: how the organization...
TabMF: Learning Dataset Representations with Tabular Foundation Models
Representations of supervised datasets serve as a foundation for higher-level machine-learning tasks such as dataset retrieval and distribution-shift monitoring. In practice, practitioners have needed reliable ways to characterize...
Spanning Diffusion and Flow-based Posterior Sampling via Exact Gaussian Conditioning
Flow-matching and diffusion models have become priors for linear inverse problems, yet most methods remain bespoke to a single class of trajectory prior. Plug-and-play alternatives exist but implicitly decorrelate the guided traje...
QTestBench: A Test Framework for Evaluating LLM-Generated Quantum Code
Large language models have shown strong results in classical code generation and are increasingly used to write unit tests that safeguard that code. Whether they can do the same for quantum software is less clear, because quantum...
AI agents in a stand-up call
Agents in a Stand-up Format Your AI agents, in a stand-up call. See who is waiting on whom and who is blocked, at zero token cost. Agent Standup turns your Claude Code session into a live team meeting: the lead gives orders, sub-a...