Tag: cs.DC
arXiv:2602.21224v1 Announce Type: cross Abstract: Speculative decoding has emerged as a pivotal technique to accelerate LLM inference by employing a lightweight draft model to generate …
arXiv:2602.22718v1 Announce Type: new Abstract: Reinforcement Learning from Human Feedback (RLHF) has been widely applied to Large Language Model (LLM) post-training to align model outputs …
arXiv:2602.18531v1 Announce Type: new Abstract: The energy management problem in the context of smart grids is inherently complex due to the interdependencies among diverse system …
arXiv:2602.15510v1 Announce Type: new Abstract: Federated Learning (FL) enables distributed training across multiple clients without centralized data sharing, while Graph Neural Networks (GNNs) model relational …
arXiv:2602.13486v1 Announce Type: new Abstract: Federated low-rank adaptation (FedLoRA) has facilitated communication-efficient and privacy-preserving fine-tuning of foundation models for downstream tasks. In practical federated learning …
