This is a report on the NSF Future Directions Workshop on Automatic Evaluation of Dialog.
The workshop explored the current state of the art along with its limitations and suggested …

Aspect-based sentiment analysis (ABSA) is a fine-grained sentiment analysis task that aims
to align aspects and corresponding sentiments for aspect-specific sentiment polarity …

A dialogue is essentially a multi-turn interaction among interlocutors. Effective evaluation
metrics should reflect the dynamics of such interaction. Existing automatic metrics are …

Automatic evaluation metrics are a crucial component of dialog systems research. Standard
language evaluation metrics are known to be ineffective for evaluating dialog. As such …

With the rapid progress of deep neural models and the explosion of available data
resources, dialogue systems that supports extensive topics and chit-chat conversations are …

Aspect-level sentiment analysis is a fine-grained sentiment classification task that aims to
identify the sentiment polarity of specific aspects in online reviews. Attention mechanisms …

As conversational models become increasingly available to the general public, users are
engaging with this technology in social interactions. Such unprecedented interaction …

Many automatic evaluation metrics have been proposed to score the overall quality of a
response in open-domain dialogue. Generally, the overall quality is comprised of various …

Human evaluation is increasingly critical for assessing large language models, capturing
linguistic nuances, and reflecting user preferences more accurately than traditional …

Recent advancements in reference-free learned metrics for open-domain dialogue
evaluation have been driven by the progress in pre-trained language models and the …