3 accepted papers
Cross-device Federated Learning (FL) is frequently bottlenecked by the prohibitive computational and communication costs of training deep neural networks on resource-constrained edge hardware. While federated dynamic pruning aims to alleviate these costs by adjusting sparse topologies during trainin…
Diffusion Language Models (DLMs) have recently emerged as a strong alternative to autoregressive language models (AR-LMs), due to their comparable accuracy and faster inference speed via parallel decoding. However, standard DLM decoding strategies, which rely on unmasking only high-confidence tokens…
Contemporary AI safety is increasingly a full-stack discipline. It spans pretraining interventions, post-training alignment (instruction tuning, RLHF and preference-optimization variants), and deployment-time controls (guardrails, monitoring, and red-teaming). This paper argues these efforts optimiz…