9 accepted papers
Large Language Models (LLMs) are prone to generating incorrect or outdated information, thereby necessitating efficient and precise mechanisms for knowledge updates. Existing knowledge editing approaches, however, often encounter conflicts between two competing objectives: maintaining existing knowl
Metalenses have been widely recognized as a key building block of next-generation optical systems, offering unprecedented advantages in compactness, lightweight design, and scalable manufacturing compared to traditional refractive optics. Despite this promise, practical use is limited by optical abe
Most Human-Machine Interaction (HMI) research overlooks the maneuvering needs of passengers in autonomous driving (AD). Natural language offers an intuitive interface, yet translating passenger open-ended instructions into control signals--without sacrificing interpretability and traceability--remai
Metalenses offer compelling advantages such as lightweight and ultra-thin design, making them promising alternatives to conventional lenses. However, their widespread adoption is hindered by image quality degradation caused by chromatic and angular aberrations. To mitigate this, restoration processe
Despite being trained on balanced datasets, existing AI-generated image detectors often exhibit systematic bias at test time, frequently misclassifying fake images as real. We hypothesize that this behavior stems from distributional shift in fake samples and implicit priors learned during training.
Robots are increasingly expected to manipulate objects, of which properties have high perceptual uncertainty from any single sensory modality. This directly impacts successful object manipulation. Object packing is one of the challenging tasks in robot manipulation. In this work, a new visuo-tactile
Active object detection (AOD) offers significant advantage in expanding the perceptual capacity of a robotics system. AOD is formulated as a sequential action decision process to determine optimal viewpoints to identify objects of interest in a visual scene. While reinforcement learning (RL) has bee
Episodic event memory is a key component of human cognition. Predicting event memorability,i.e., to what extent an event is recalled, is a tough challenge in memory research and has profound implications for artificial intelligence. In this study, we investigate factors that affect event memorabilit…
Active vision is a desirable perceptual feature for robots. Existing approaches usually make strong assumptions about the task and environment, thus are less robust and efficient. This study proposes an adaptive view planning approach to boost the efficiency and robustness of active object detection…