The advent of large language models marks a revolutionary breakthrough in artificial
intelligence. With the unprecedented scale of training and model parameters, the capability …

The task of resolving repeated objects in natural languages is known as coreference
resolution, and it is an important part of modern natural language processing. It is classified …

Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the
field of natural language processing and artificial intelligence, due to their emergent ability …

While coreference resolution typically involves various linguistic challenges, recent models
are based on a single pairwise scorer for all types of pairs. We present LingMess, a new …

Cross-document event coreference resolution (CD-ECR) is a task of clustering event
mentions across multiple documents that refer to the same real-world events. Previous …

Event coreference models cluster event mentions pertaining to the same real-world event.
Recent models rely on contextualized representations to recognize coreference among …

Event Coreference Resolution (ECR) is the task of linking mentions of the same event either
within or across documents. Most mention pairs are not coreferent, yet many that are …

We introduce iFacetSum, a web application for exploring topical document sets. iFacetSum
integrates interactive summarization together with faceted search, by providing a novel …

We point out that common evaluation practices for cross-document coreference resolution
have been unrealistically permissive in their assumed settings, yielding inflated results. We …

Identifying related entities and events within and across documents is fundamental to natural
language understanding. We present an approach to entity and event coreference …