Zobrazeno 1 - 10
of 4 695
pro vyhledávání: '"HU, HAN"'
Recent advancements in multimodal fusion have witnessed the remarkable success of vision-language (VL) models, which excel in various multimodal applications such as image captioning and visual question answering. However, building VL models requires
Externí odkaz:
http://arxiv.org/abs/2410.17779
Incremental learning is nontrivial due to severe catastrophic forgetting. Although storing a small amount of data on old tasks during incremental learning is a feasible solution, current strategies still do not 1) adequately address the class bias pr
Externí odkaz:
http://arxiv.org/abs/2409.05620
This paper considers a multi-functional orthogonal frequency division multiplexing (OFDM) system with integrated sensing, communication, and powering (ISCAP), in which a multi-antenna base station (BS) transmits OFDM signals to simultaneously deliver
Externí odkaz:
http://arxiv.org/abs/2408.14156
Deep model training on extensive datasets is increasingly becoming cost-prohibitive, prompting the widespread adoption of deep model fusion techniques to leverage knowledge from pre-existing models. From simple weight averaging to more sophisticated
Externí odkaz:
http://arxiv.org/abs/2408.10174
In a real federated learning (FL) system, communication overhead for passing model parameters between the clients and the parameter server (PS) is often a bottleneck. Hierarchical federated learning (HFL) that poses multiple edge servers (ESs) betwee
Externí odkaz:
http://arxiv.org/abs/2408.09762
In practical federated learning (FL) systems, the presence of malicious Byzantine attacks and data heterogeneity often introduces biases into the learning process. However, existing Byzantine-robust methods typically only achieve a compromise between
Externí odkaz:
http://arxiv.org/abs/2408.09539
High-quality data is crucial for the pre-training performance of large language models. Unfortunately, existing quality filtering methods rely on a known high-quality dataset as reference, which can introduce potential bias and compromise diversity.
Externí odkaz:
http://arxiv.org/abs/2408.08310
Semantic communications have been envisioned as a potential technique that goes beyond Shannon paradigm. Unlike modern communications that provide bit-level security, the eaves-dropping of semantic communications poses a significant risk of potential
Externí odkaz:
http://arxiv.org/abs/2408.02095
Unit testing is an essential component of software testing, with the assert statements playing an important role in determining whether the tested function operates as expected. Although research has explored automated test case generation, generatin
Externí odkaz:
http://arxiv.org/abs/2407.21429
Autor:
Li, Hao-En, Li, Xiang, Huang, Jia-Cheng, Zhang, Guang-Ze, Shen, Zhu-Ping, Zhao, Chen, Li, Jun, Hu, Han-Shi
The matrix product state (MPS) ansatz offers a promising approach for finding the ground state of molecular Hamiltonians and solving quantum chemistry problems. Building on this concept, the proposed technique of quantum circuit MPS (QCMPS) enables t
Externí odkaz:
http://arxiv.org/abs/2407.10523