3 accepted papers
Existing modification-based linguistic steganography methods primarily perform linguistic manipulations within a single embedding space to conceal secret information. However, these methods are stringently constrained by the original semantics of the cover text, making it struggle to achieve a satis…
One major challenge in weakly supervised learning is learning from inexact supervision, ranging from partial labels (PLs) with *redundant* information to the extreme of unlabeled data with *insufficient* information. While recent work has made significant strides in specific inexact supervision cont…
A partial label (PL) specifies a set of candidate labels for an instance and partial-label learning (PLL) trains multi-class classifiers with PLs. Recently, many methods that incorporate techniques from other domains have shown strong potential. The expectation that stronger techniques would enhance…