With the rapid development of the Internet of Things (IoT), federated learning (FL) has gained increasing attention for its privacy-preserving use of distributed data. However, conventional two-tier FL architectures are poorly suited to the hierarchical and heterogeneous nature of real-world IoT systems. Hierarchical...
Jie-Chao Gao, Yuan-Gang Li, Jie Wang et al.· npj Artificial Intelligence· 1 citation
This work proposes MetaPersona, a framework that retrieves task-relevant evidence, constructs literature-derived persona dependency graphs, and samples synthetic populations from empirical priors linking demographics, latent attributes, and outcomes.
Jin Ye, Yuan-Gang Li, Chen-Xiao Yu et al.· 0 citations
STRAT is introduced, which partitions the residual stream into orthogonal Data and Type subspaces and uses Type-based attention and gating to govern Data transformations and in arithmetic, STRAT reduces median OOD error 35-fold relative to a Transformer baseline.
Cristina V. Lopes, Yuan-Gang Li, Justin Tian Jin Chen et al.· 0 citations
Harbor Adapters are developed that port more than 80 benchmarks to evaluate arbitrary agents, and validated through rigorous code review and parity experiments, and Harbor-Index is introduced, a curated set of 82 difficult, diverse, and high-quality tasks spanning 29 benchmarks to support more reliable and comprehensiv...
Lin Shi, Hao-Wei Lin, Zi-Xuan Zhu et al.· 1 citation
This work introduces CodeRQ-Bench, the first benchmark for evaluating LLM reasoning quality across three coding task categories: generation, summarization, and classification, and proposes VERA, a two-stage evaluator that combines evidence-grounded verification with ambiguity-aware score correction.
Yuangang Li, Justin Tian Jin Chen, Ethan Yu et al.· arXiv.org· 1 citation
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
