2 citations · 3 across the 5 of their papers we have counts for
3 papers · 2 filters
Chained Tuning Leads to Biased Forgetting
Megan Ung, Alicia Sun, Samuel J. Bell +3
Large language models (LLMs) are often fine-tuned for use on downstream tasks, though this can degrade capabilities learned during previous training. This phenomenon, often referre…
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…
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…