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cs.CL2024
Improving Model Evaluation using SMART Filtering of Benchmark Datasets
Vipul Gupta, Candace Ross, David Pantoja +3
One of the most challenging problems facing NLP today is evaluation. Some of the most pressing issues pertain to benchmark saturation, data contamination, and diversity in the qual…
cs.CL2024★ 2 cited
ESPERANTO: Evaluating Synthesized Phrases to Enhance Robustness in AI Detection for Text Origination
Navid Ayoobi, Lily Knab, Wen Cheng +5
While large language models (LLMs) exhibit significant utility across various domains, they simultaneously are susceptible to exploitation for unethical purposes, including academi…
cs.CL2024
Changing Answer Order Can Decrease MMLU Accuracy
Vipul Gupta, David Pantoja, Candace Ross +2
As large language models (LLMs) have grown in prevalence, particular benchmarks have become essential for the evaluation of these models and for understanding model capabilities. M…