2 citations · 4 across the 10 of their papers we have counts for
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cs.CL2024★ 1 cited
SG-Bench: Evaluating LLM Safety Generalization Across Diverse Tasks and Prompt Types
Yutao Mou, Shikun Zhang, Wei Ye
Ensuring the safety of large language model (LLM) applications is essential for developing trustworthy artificial intelligence. Current LLM safety benchmarks have two limitations.…
cs.CL2024★ 2 cited
HelloBench: Evaluating Long Text Generation Capabilities of Large Language Models
Haoran Que, Feiyu Duan, Liqun He +11
In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities in various tasks (e.g., long-context understanding), and many benchmarks have been proposed.…