Zobrazeno 1 - 10
of 171 149
pro vyhledávání: '"Tung, A."'
Autor:
Pham, Duy-Tung, Vu, Thien Trang Nguyen, Nguyen, Tung, Van, Linh Ngo, Nguyen, Duc Anh, Nguyen, Thien Huu
Recent advances in neural topic models have concentrated on two primary directions: the integration of the inference network (encoder) with a pre-trained language model (PLM) and the modeling of the relationship between words and topics in the genera
Externí odkaz:
http://arxiv.org/abs/2409.19749
Semantic text embedding is essential to many tasks in Natural Language Processing (NLP). While black-box models are capable of generating high-quality embeddings, their lack of interpretability limits their use in tasks that demand transparency. Rece
Externí odkaz:
http://arxiv.org/abs/2410.03435
Recent work in offline reinforcement learning (RL) has demonstrated the effectiveness of formulating decision-making as return-conditioned supervised learning. Notably, the decision transformer (DT) architecture has shown promise across various domai
Externí odkaz:
http://arxiv.org/abs/2410.03408
Recent studies reveal that well-performing reinforcement learning (RL) agents in training often lack resilience against adversarial perturbations during deployment. This highlights the importance of building a robust agent before deploying it in the
Externí odkaz:
http://arxiv.org/abs/2410.03376
Selective state space models (SSM), such as Mamba, have gained prominence for their effectiveness in modeling sequential data. Despite their outstanding empirical performance, a comprehensive theoretical understanding of deep selective SSM remains el
Externí odkaz:
http://arxiv.org/abs/2410.03292
Disruptions to medical infrastructure during disasters pose significant risks to critically ill patients with advanced chronic kidney disease or end-stage renal disease. To enhance patient access to dialysis treatment under such conditions, it is cru
Externí odkaz:
http://arxiv.org/abs/2410.02956
In this paper, we give a definition of weak stability condition on a triangulated category. The difference between our definition and existing definitions is that we allow objects in the kernel to have non-maximal phases. We then construct four types
Externí odkaz:
http://arxiv.org/abs/2410.02466
Autor:
Wu, Tung-Yu, Lo, Pei-Yu
Large language models (LLMs) have been shown to exhibit emergent abilities in some downstream tasks, where performance seems to stagnate at first and then improve sharply and unpredictably with scale beyond a threshold. By dividing questions in the d
Externí odkaz:
http://arxiv.org/abs/2410.01692
The scalability limitations of Transformers regarding sequence length have renewed interest in recurrent sequence models that are parallelizable during training. As a result, many novel recurrent architectures, such as S4, Mamba, and Aaren, have been
Externí odkaz:
http://arxiv.org/abs/2410.01201
We investigate operator dynamics and entanglement growth in dual-unitary circuits, a class of locally scrambled quantum systems that enables efficient simulation beyond the exponential complexity of the Hilbert space. By mapping the operator evolutio
Externí odkaz:
http://arxiv.org/abs/2410.00953