Author

Ze-Yu Zhang

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#artificial intelligence Jun 2026

Connect the Dots: Training LLMs for Long-Lifecycle Agents with Cross-Domain Generalization Via Reinforcement Learning

This work presents a general framework for training large language models (LLMs) to "Connect the Dots", a meta-capability required by long-lifecycle agents, and presents proof-of-concept implementations of the CoD framework, including a GRPO-style RL algorithm with fine-grained credit assignment.

Yan-Xi Chen, Wei-Jie Shi, Bo Hu et al. · arXiv.org · 0 citations

Preprint Aug 2026

When Names Cross Scripts: A Source-Grounded Benchmark for Historical Entity Reconciliation in the Mongol World

Historical people may appear under different languages, scripts, and transcription traditions, while distinct individuals may share highly similar or even identical names. This makes historical identity reconciliation more than a problem of string matching or transliteration. We introduce MHER, a provenance-controlled...

Xiang-Nan Chen, Ze-Yu Zhang · 0 citations

Open access Jul 2026

Textual overlap rather than domain alignment: A comparative study of fine-tuning strategies for specialised machine translation with large language models

Findings indicate that textual overlap between training and deployment data, rather than broad domain similarity alone, strongly conditions the observed benefit of fine-tuning.

Lixue Yang, Jiaxin Zhu, Ze-Yu Zhang · PLoS ONE · 0 citations