Author

Jing Liu

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#machine learning Preprint Sep 2026

Which Models Work Well Together? Measuring Heterogeneity for LLM Team Selection

The performance ceiling of an LLM team is constrained not only by individual model capabilities, but also by inter-member error resonance and predictive differences. Although heterogeneous teaming is often observed to be effective in practice, existing approaches lack complementarity metrics that are computable, interp...

Liang-Yu Teng, Heng-Song Liu, Jun-Cen Guo et al. · 0 citations

#machine learning Jul 2026

Continual Learning with Elastic Regularization and Synthetic Replay for Federated MLLM Fine-Tuning

Federated Continual Multimodal Learning (FedCMM), a framework that embeds continual-learning safeguards into the federated optimization loop at three complementary levels, is proposed, confirming that holistic, modality-aware optimization enables robust evolutive adaptation across heterogeneous networked AI deployments...

Jing Liu, Chenxuanyi Zou, Jiayang Ren et al. · arXiv.org · 0 citations