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Jing-Ting Zheng

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#artificial intelligence Preprint Oct 2026

ABench: Adversarily Benchmarking Large Language Models across Taxonomized Values

Ensuring the alignment of Large Language Models (LLMs) with diverse cultural values is critical for their safe global deployment. However, existing alignment benchmarks are predominantly English-centric or confined to simple discriminative tasks. Moreover, they often fail to effectively evaluate model robustness agains...

Li-Ping Yang, Yong-Qi Leng, Jing-Ting Zheng et al. · 0 citations
#natural language process... Preprint Oct 2026

VALCON: Benchmarking and Enhancing Value Consistency in Large Language Models via Dual-Role Variation

Current value alignment evaluations for large language models (LLMs) heavily rely on output compliance, overlooking whether LLMs maintain value consistency when alternating between generator and evaluator roles. Such consistency is increasingly important because modern LLM agents and alignment pipelines often rely on t...

Jun-Ru Wu, Jing-Ting Zheng, Yu-Qi Ren et al. · 0 citations

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