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Annotating Errors in English Learners' Written Language Production: Advancing Automated Written Feedback Systems
Steven Coyne, Diana Galvan-Sosa, Ryan Spring +4
Recent advances in natural language processing (NLP) have contributed to the development of automated writing evaluation (AWE) systems that can correct grammatical errors. However,…
cs.CL2025
Rubrik's Cube: Testing a New Rubric for Evaluating Explanations on the CUBE dataset
Diana Galvan-Sosa, Gabrielle Gaudeau, Pride Kavumba +5
The performance and usability of Large-Language Models (LLMs) are driving their use in explanation generation tasks. However, despite their widespread adoption, LLM explanations ha…