We invite papers on any topic related to the evaluation of NLG systems, including (but not limited to):

• Qualitative studies, definitions of evaluation metrics (e.g., readability, fluency, semantic correctness)
• Crowdsourcing Strategies, qualitative tests for crowdsourcing (How to elucidate evaluation metrics?)
• Looking at individual differences and cognitive biases in human evaluation (expert vs. non-expert, L1 vs L2 speakers)
• Best practices for system evaluations (How does your lab choose models?)
• Qualitative study/error analysis approaches
• Demo: Systems that make the evaluation easier
• Comparison of metrics across different NLG tasks (captioning, data2text, story generation, summarization…) or different languages (with a focus on low-resource languages)
• Evaluation surveys
• Opinion pieces and commentary on trends in evaluation