Yu Fu

DiagramRAG is a lightweight retrieval-augmented framework that uses reference diagrams to guide the completion of scientific diagrams from incomplete user sketches, achieving high performance on standard benchmarks.

UI-KOBE is a framework that enhances lightweight mobile GUI agents by integrating reusable, app-specific knowledge graphs, allowing them to perform complex tasks efficiently on-device without relying on large vision-language models.

The paper introduces DSL-LLaDA, a method that lightly adapts a pre-trained masked diffusion language model to perform continuous denoising in embedding space, significantly improving text generation quality and robustness, especially under low step budgets.

The paper introduces D3IM, a novel parameter-free sampler that enables direct revision of visible tokens in Masked Diffusion Language Models, and proposes SCOPE to mitigate the model's tendency to perpetuate errors.

D-Judge introduces a semantics-preserving output rewriting defense that disrupts multi-turn jailbreak attacks by misaligning the feedback signal used by an attacker's judge model.

This paper proposes IOHMM-BO, a method using a high-order input-output hidden Markov model with Bayesian optimization for predictive dynamic power management in 5G NR user equipment, achieving 43% energy saving with low computational overhead.