5 accepted papers
In competitive programming task, problem statements are often embedded within elaborate narrative backgrounds, requiring deep understanding of the underlying solutions to successfully complete the tasks. Current code generation models primarily focus on token-level semantic modeling, highly suscepti
Federated learning is susceptible to model poisoning attacks, especially those meticulously crafted for servers. Traditional defense methods mainly focus on updating assessments or robust aggregation against manually crafted myopic attacks. When facing advanced attacks, their defense stability is no…
Stealthy data poisoning during fine-tuning can backdoor large language models (LLMs), threatening downstream safety. Existing detectors either use classifier-style probability signals—ill-suited to generation—or rely on rewriting, which can degrade quality and even introduce new triggers. We address
Neural implicit methods have made remarkable progress in 3D reconstruction. However, previous methods often assume view-independent properties of target objects, which fails to accurately reconstruct objects with challenging characteristics, such as transparency and high reflectivity. To address thi…
Recent advances in 3D Gaussian Splatting (3DGS) have improved the visual fidelity of dynamic avatar reconstruction. However, existing methods often overlook the inherent chromatic similarity of human skin tones, leading to poor capture of intricate facial geometry under subtle appearance changes. Th…