5 accepted papers
Classes, as fundamental elements of Computer Vision, have been extensively studied within incremental learning frameworks. In contrast, tokens, which play essential roles in many research fields, exhibit similar characteristics of growth, yet investigations into their incremental learning remain sig
Open-set active learning (OSAL) aims to identify informative samples for annotation when unlabeled data may contain previously unseen classes--a common challenge in safety-critical and open-world scenarios. Existing approaches typically rely on separately trained open-set detectors, introducing subs
Gene Regulatory Network (GRN) inference is essential for understanding complex cellular mechanisms, rendered tractable through single-cell transcriptomic data. With the emergence of single-cell Foundation Models (scFMs), enhanced transcriptomic encoding is widely expected to revolutionize GRN infere…
Single-cell transcriptomics describes complex molecular features at the individual cell level, serving various roles in biological research, such as enhancing gene expression and predicting drug responses. Due to transcriptomic data structurally resembling sequential data, many researchers have trai…
For binocular stereo, traditional cameras excel in capturing fine details and texture information but are limited in terms of dynamic range and their ability to handle rapid motion. On the contrary, event cameras provide pixel-level intensity changes with low latency and a wide dynamic range, albeit…