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cs.AI2026
Data Science and Technology Towards AGI Part I: Tiered Data Management
Yudong Wang, Zixuan Fu, Hengyu Zhao +14
The development of artificial intelligence can be viewed as an evolution of data-driven learning paradigms, with successive shifts in data organization and utilization continuously…
cs.CL2026
Small Updates, Big Doubts: Does Parameter-Efficient Fine-tuning Enhance Hallucination Detection ?
Xu Hu, Yifan Zhang, Songtao Wei +4
Parameter-efficient fine-tuning (PEFT) methods are widely used to adapt large language models (LLMs) to downstream tasks and are often assumed to improve factual correctness. Howev…
cs.CL2026
Factuality on Demand: Controlling the Factuality-Informativeness Trade-off in Text Generation
Ziwei Gong, Yanda Chen, Julia Hirschberg +4
Large language models (LLMs) encode knowledge with varying degrees of confidence. When responding to queries, models face an inherent trade-off: they can generate responses that ar…