3 papers
cs.CL2025
Arbiters of Ambivalence: Challenges of Using LLMs in No-Consensus Tasks
Bhaktipriya Radharapu, Manon Revel, Megan Ung +2
The increasing use of LLMs as substitutes for humans in ``aligning'' LLMs has raised questions about their ability to replicate human judgments and preferences, especially in ambiv…
cs.CL2024
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…
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…