4 accepted papers
Non-Markovian Tasks (NMTs) are distinguished by their dependence on long-term memory and state-dependent dynamics, setting them apart from the traditional Markovian models typically employed in Reinforcement Learning (RL). NMTs not only suffer from reward sparseness but also rely on historical infor
The research in AI-based formal mathematical reasoning has shown an unstoppable growth trend. These studies have excelled in mathematical competitions like IMO and have made significant progress. However, these studies intertwined multiple skills simultaneously—problem-solving, reasoning, and writin…
Deep neural networks (DNNs) have become integral to numerous safety-critical applications, necessitating rigorous verification of their trustworthiness. However, the problem of verifying DNNs has high computational complexity, and existing techniques have limited efficiency, insufficient to deal wit
"Adversarial training (AT) has become an effective defense method against adversarial examples (AEs) and it is typically framed as a bi-level optimization problem. Among various AT methods, fast AT (FAT), which employs a single-step attack strategy to guide the training process, can achieve good rob…