10 accepted papers
Large Language Models (LLMs) often struggle to align their responses with objective facts, resulting in the issue of factual hallucinations , which can be difficult to detect and mislead users without relevant knowledge. Although post-training techniques have been employed to mitigate the issue, exi
Output uncertainty indicates whether the probabilistic properties of the overall distribution reflect objective characteristics of the model output. Unlike most loss functions and metrics in machine learning, uncertainty pertains to individual samples, but validating it on individual samples is unfe…
Earth observation foundation models have shown strong generalization across multiple Earth observation tasks, but their robustness under real-world perturbations remains underexplored. To bridge this gap, we introduce REOBench, the first comprehensive benchmark for evaluating the robustness of Earth…
Ensuring the safety and harmlessness of Large Language Models (LLMs) has become equally critical as their performance in applications. However, existing safety alignment methods typically suffer from safety-performance trade-offs and susceptibility to jailbreak attacks, primarily due to their relian…
Diffusion models have shown significant potential for image style transfer tasks. However, achieving effective stylization while preserving content in a training-free setting remains a challenging issue due to the tightly coupled representation space and inherent randomness of the models. In this pa
Modern deep learning models often exhibit overconfident predictions, inadequately capturing uncertainty. During model optimization, the expected calibration error tends to overfit earlier than classification accuracy, indicating distinct optimization objectives for classification error and calibrat…
Although Multimodal Large Language Models (MLLMs) have demonstrated promising versatile capabilities their performance is still inferior to specialized models on downstream tasks which makes adaptation necessary to enhance their utility. However fine-tuning methods require independent training for e…
Teleoperation systems with haptic feedback allow a human user to remotely interact with a dangerous or inac-cessible environment, perform various tasks, and perceive the haptic feedback. To ensure system stability while maintaining the best possible quality of experience (QoE), different teleoperati…
How to select between policies and value functions produced by different training algorithms in offline reinforcement learning (RL)---which is crucial for hyperparameter tuning---is an important open question. Existing approaches based on off-policy evaluation (OPE) often require additional function…
Fluorescence microscopy has enabled a dramatic development in modern biology. Due to its inherently weak signal, fluorescence microscopy is not only much noisier than photography, but also presented with Poisson-Gaussian noise where Poisson noise, or shot noise, is the dominating noise source. To ge…