This tutorial surveys neural approaches to conversational AI that were developed in the last
few years. We group conversational systems into three categories:(1) question answering …

There is a resurgent interest in developing intelligent open-domain dialog systems due to
the availability of large amounts of conversational data and the recent progress on neural …

Current developments in large language models (LLMs) have enabled impressive zero-shot
capabilities across various natural language tasks. An interesting application of these …

Statistical machine translation (SMT) treats the translation of natural language as a machine
learning problem. By examining many samples of human-produced translation, SMT …

This article presents the most up-to-date, influential automated, semiautomated and human
metrics used to evaluate the quality of machine translation (MT) output and provides the …

A new metric\texttt {BaryScore} to evaluate text generation based on deep contextualized
embeddings eg, BERT, Roberta, ELMo) is introduced. This metric is motivated by a new …

The evaluation of machine-generated image captions poses an interesting yet persistent
challenge. Effective evaluation measures must consider numerous dimensions of similarity …

This paper describes a new evaluation metric, TER-Plus (TERp) for automatic evaluation of
machine translation (MT). TERp is an extension of Translation Edit Rate (TER). It builds on …

Large language models (LLMs) have shown promise in accelerating radiology reporting by
summarizing clinical findings into impressions. However, automatic impression generation …

Assessing the quality of candidate translations involves diverse linguistic facets. However,
most automatic evaluation methods in use today rely on limited quality assumptions, such as …