Language models: past, present, and future Page 1 56 COMMUNICATIONS OF THE ACM |
JULY 2022 | VOL. 65 | NO. 7 contributed articles NATURAL LANGUAGE PROCESSING (NLP) …

The ability to generalise well is one of the primary desiderata of natural language
processing (NLP). Yet, what'good generalisation'entails and how it should be evaluated is …

Abstract The Assessing DIScourse COherence in Italian TEXts (DisCoTEX) task is the first
shared task focused on modelling discourse coherence for Italian real-word texts, which has …

Progress in summarizing long texts is inhibited by the lack of appropriate evaluation
frameworks. When a long summary must be produced to appropriately cover the facets of …

Given the claims of improved text generation quality across various pre-trained neural
models, we consider the coherence evaluation of machine generated text to be one of the …

Extremely large volumes of documents are available from online news platforms and social
media. While the quantity of these documents have grown exponentially, the majority lack …

This paper introduces the Chinese Essay Discourse Coherence Corpus (CEDCC), a multi-
task dataset for assessing discourse coherence. Existing research tends to focus on isolated …

Coherence assessment is central to many NLP tasks, but its evaluation is complex and often
done indirectly. In the LLM era, it is even more crucial to understand how, and how well …

Coherence evaluation aims to assess the organization and structure of a discourse, which
remains challenging even in the era of large language models. Due to the scarcity of …

In the era of heavy emphasis on deep neural architectures with well-proven and impressive
competencies albeit with massive carbon footprints, we present a simple and inexpensive …