End-to-end pipeline for automated heart failure diagnosis with clinical notes using SNOMED-CT
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Rhetorical Questions in LLM Representations: A Linear Probing Study
arXiv:2604.14128v1 Announce Type: cross Abstract: Rhetorical questions are asked not to seek information but to persuade or signal stance. How…
ASTER: Latent Pseudo-Anomaly Generation for Unsupervised Time-Series Anomaly Detection
arXiv:2604.13924v1 Announce Type: cross Abstract: Time-series anomaly detection (TSAD) is critical in domains such as industrial monitoring, healthcare, and cybersecurity,…
Three Roles, One Model: Role Orchestration at Inference Time to Close the Performance Gap Between Small and Large Agents
arXiv:2604.11465v2 Announce Type: replace Abstract: Large language model (LLM) agents show promise on realistic tool-use tasks, but deploying capable agents…
Variance Computation for Weighted Model Counting with Knowledge Compilation Approach
arXiv:2601.03523v2 Announce Type: replace Abstract: One of the most important queries in knowledge compilation is weighted model counting (WMC), which…
FCBV-Net: Category-Level Robotic Garment Smoothing via Feature-Conditioned Bimanual Value Prediction
arXiv:2508.05153v2 Announce Type: replace-cross Abstract: Category-level generalization for robotic garment manipulation, such as bimanual smoothing, remains a significant hurdle due…
Exploration and Exploitation Errors Are Measurable for Language Model Agents
arXiv:2604.13151v1 Announce Type: new Abstract: Language Model (LM) agents are increasingly used in complex open-ended decision-making tasks, from AI coding…
Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and Recipe
arXiv:2604.13016v2 Announce Type: replace-cross Abstract: On-policy distillation (OPD) has become a core technique in the post-training of large language models,…
Beyond Conservative Automated Driving in Multi-Agent Scenarios via Coupled Model Predictive Control and Deep Reinforcement Learning
arXiv:2604.13891v1 Announce Type: cross Abstract: Automated driving at unsignalized intersections is challenging due to complex multi-vehicle interactions and the need…
Evaluating Supervised Machine Learning Models: Principles, Pitfalls, and Metric Selection
arXiv:2604.13882v1 Announce Type: cross Abstract: The evaluation of supervised machine learning models is a critical stage in the development of…