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cs.CL2026
RankLLM: Weighted Ranking of LLMs by Quantifying Question Difficulty
Ziqian Zhang, Xingjian Hu, Yue Huang +8
Benchmarks establish a standardized evaluation framework to systematically assess the performance of large language models (LLMs), facilitating objective comparisons and driving ad…
cs.CL2025★ 2 cited
RAG LLMs are Not Safer: A Safety Analysis of Retrieval-Augmented Generation for Large Language Models
Bang An, Shiyue Zhang, Mark Dredze
Efforts to ensure the safety of large language models (LLMs) include safety fine-tuning, evaluation, and red teaming. However, despite the widespread use of the Retrieval-Augmented…
cs.CL2024
Exploring Adversarial Robustness in Classification tasks using DNA Language Models
Hyunwoo Yoo, Haebin Shin, Kaidi Xu +1
DNA Language Models, such as GROVER, DNABERT2 and the Nucleotide Transformer, operate on DNA sequences that inherently contain sequencing errors, mutations, and laboratory-induced…