arXiv:2604.00076v1 Announce Type: cross
Abstract: Reinforcement Learning (RL) agents often struggle with efficiency and performance in complex environments. We propose a novel framework that uses a Large Language Model (LLM) to dynamically generate a …
arXiv:2604.00809v1 Announce Type: new
Abstract: Building on existing approaches, we revisit Human-in-the-Loop Object Retrieval, a task that consists of iteratively retrieving images containing objects of a class-of-interest, specified by a user-provid…
arXiv:2604.00779v1 Announce Type: cross
Abstract: Label prediction in neural networks (NNs) has O(n) complexity proportional to the number of classes. This holds true for classification using fully connected layers and cosine similarity with some set …
arXiv:2604.00073v1 Announce Type: cross
Abstract: There has been growing interest in building agents that can interact with digital platforms to execute meaningful enterprise tasks autonomously. Among the approaches explored are tool-augmented agents …
arXiv:2604.00799v1 Announce Type: cross
Abstract: Spatial consistency is a fundamental property of the visual world and a key requirement for models that aim to understand physical reality. Despite recent advances, multimodal large language models (ML…
arXiv:2603.26461v2 Announce Type: replace-cross
Abstract: Process anomaly detection is an important application of process mining for identifying deviations from the normal behavior of a process. Neural network-based methods have recently been applied…
arXiv:2604.00557v1 Announce Type: cross
Abstract: The generalization ability of imitation learning policies for robotic manipulation is fundamentally constrained by the diversity of expert demonstrations, while collecting demonstrations across varied …
arXiv:2604.00072v1 Announce Type: cross
Abstract: Can classifier-based safety gates maintain reliable oversight as AI systems improve over hundreds of iterations? We provide comprehensive empirical evidence that they cannot. On a self-improving neural…
arXiv:2603.20897v2 Announce Type: replace-cross
Abstract: The strong and continuous increase of AI-based services leads to the steady proliferation of AI data centres worldwide with the unavoidable escalation of their power consumption. It is unknown …
arXiv:2604.00792v1 Announce Type: new
Abstract: Accurate 3D dental imaging is vital for diagnosis and treatment planning, yet CBCT’s high radiation dose and cost limit its accessibility. Reconstructing 3D volumes from a single low-dose panoramic X-ray…